Research Article Design and Experimental Evaluation of a ...position control system, a number of...
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Hindawi Publishing CorporationThe Scientific World JournalVolume 2013 Article ID 590708 16 pageshttpdxdoiorg1011552013590708
Research ArticleDesign and Experimental Evaluation of a RobustPosition Controller for an Electrohydrostatic ActuatorUsing Adaptive Antiwindup Sliding Mode Scheme
Ji Min Lee Sung Hwan Park and Jong Shik Kim
School of Mechanical Engineering Pusan National University Jangjeon-dong Geumjeong-guBusan 609-732 Republic of Korea
Correspondence should be addressed to Jong Shik Kim jskimpnuedu
Received 13 May 2013 Accepted 5 June 2013
Academic Editors U Lee and S Liu
Copyright copy 2013 Ji Min Lee et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited
A robust control scheme is proposed for the position control of the electrohydrostatic actuator (EHA) when considering hardwaresaturation load disturbance and lumped systemuncertainties and nonlinearities To reduce overshoot due to a saturation of electricmotor and to realize robustness against load disturbance and lumped systemuncertainties such as varying parameters andmodelingerror this paper proposes an adaptive antiwindup PID sliding mode scheme as a robust position controller for the EHA systemAn optimal PID controller and an optimal anti-windup PID controller are also designed to compare control performance An EHAprototype is developed carrying out systemmodeling and parameter identification in designing the position controllerThe simplyidentified linear model serves as the basis for the design of the position controllers while the robustness of the control systems iscompared by experiments The adaptive anti-windup PID sliding mode controller has been found to have the desired performanceand become robust against hardware saturation load disturbance and lumped system uncertainties and nonlinearities
1 Introduction
Recently lots of hydraulic servo systems have been replacedby electric motor-driven systems to overcome the drawbacksof traditional hydraulic servo systems such as oil leakagemaintenance and laying complex pipe In spite of these draw-backs hydraulic systems are still used in fields that requirelarge force and high power In order to solve these issues elec-trohydrostatic actuator (EHA) systems are in the process ofbeing developed for industrial useThe EHA systems can alsobe referred to as a direct drive volume controlled (DDVC)actuator [1ndash3] or valveless hydraulic servo (VHS) actuator [4]
The EHA systems generally consist of an electric motorhydraulic pump hydraulic cylinder accumulator checkvalves and relief valves for safety An electric motor thatis directly tied to the hydraulic pump controls the cylinderwhose directional change depends upon the electric motorrsquosrotation direction Also an electric motor installed in theEHA system controls the flow rate and pressure of the work-ing fluid by regulating the velocity and torque of the motor
The EHA systems are kind of compact high-poweractuator modules that integrate the electric motor hydraulicpump hydraulic cylinder accumulator check valves andrelief valves into one component by using themanifold blockCompared to conventional hydraulic systems EHAs are verysmall and do not need complex pipe lines The EHA systemsare seen as environment-friendly hydraulic servo systembecause it does not leak oil
The main advantage of using EHA systems on the wholecomes from its increased energy efficiency [5ndash10] The EHAsystems designed in this research do not use any controlvalves such as a servo valve and can also supply theminimumenergy needed for the hydraulics system by controlling theservo motor meaning that the EHA systems are extremelyenergy efficient Also by using an electric servo motor asa control device EHA systems can quickly achieve fastresponse and high accuracy However since the EHA systemsare a kind of hydraulic servo system it has nonlinearityrelated to the friction force mainly located in the hydrauliccylinderTheEHAsystemalso has the closed hydraulic circuit
2 The Scientific World Journal
which can use relatively little working fluidThe performanceof the EHA system can also be sensitive to variation withinthe system parameters of the working fluid such as varietyof effective bulk modulus and the leakage coefficient due tochanges in the working environment [5 7 9 11ndash13] Thosenonlinearity and uncertainty may cause the position controlsystem of the EHA to be unstable or have a much degradedperformance
In order to obtain the desirable performance of an EHAposition control system a number of control strategies havebeen applied and investigated by many researchers Some ofthe work has used linear control theory for the position con-trol of EHA [14ndash16] The nonlinear robust control schemessuch as sliding mode control back-stepping control andFuzzy logic control have been proposed to achieve robustnessof position control system for EHA by compensating systemnonlinearity and uncertainties and to compensate for thenonlinear dynamics of EHA system such as friction [3 5 6 9ndash11 14 17 18] Adaptive control approaches have been also pro-posed to make up for parameter disturbances such as varyingthe viscous friction coefficient and the effective bulkmodulusdue to change of working condition [1ndash3 9 11 19 20]
However a fast response with small overshoot should bethe objective for the practical use of the EHA position controlsystems in industrial machine such as plastic injection mold-ing machine aircraft actuation system mobile machineryCNC pipe bending machines and hydraulic servo controlof steering system for ship and hydraulic press [1 2] eventhough there are lots of uncertainties and nonlinearity inposition control system of EHA The problem concerninglarge overshoot from the saturation in the electric motor hasbeen considered in recent studies [2] In [2] the saturationof voltage and current of the PWM driver and DC poweris taken into account for position control system of EHAThe researchers of [2] also consider dead zone torque due tothe static friction of motor pump and variable load torqueThe PD-PI hybrid control scheme is proposed to controlthe BLDC motor in order to achieve small overshoot andto compensate for the load disturbances However only acomputer simulation can verify the proposed linear controlscheme although there are lots of uncertainty and nonlinear-ity besides the dead zone and motor saturation In [2 19]they proposed a self-turning Fuzzy PID control scheme tocompensate for the dead zone saturation of motor angularvelocity parameter uncertainties and load disturbance withexperimental verification However improved accuracy andfast response appear necessary to apply the position controlresults to servo press Also the design of fuzzy rules dependslargely on the experience of experts or input-output data
In this research an adaptive antiwindup PID slidingmode control scheme is proposed to solve problems ofovershoot in position control caused by saturation of angu-lar velocity to the electric motor The previous researchesconsidered an antiwindup scheme based on the conventionalsliding mode controller [21 22] However the proposedcontroller consists of an adaptive control and a conventionalsliding mode control with antiwindup scheme Thereforethe proposed control scheme looks to implement robustnessto parameter variations in a variety of working condition
nonlinearity and load disturbance The validation of theproposed control scheme is verified by experiment
This paper will proceed as follows Section 2 reveals thecomposition and details of the position control test rig of anEHA prototype followed by systemmodeling and parameteridentification of the EHA systems in Section 3 In Section 4position controllers for the EHA system using traditionalPID antiwindup PID and adaptive antiwindup PID slidingmode control schemes are presentedThe comparative resultsof the experimental tests executed on the position controltest rig of EHA applying PID antiwindup PID and adaptiveantiwindup PID sliding mode control schemes are revealedin Section 5 followed by conclusions in Section 6
2 Experimental Setup of the ElectrohydraulicActuator Prototype
In this study the EHA system consists of a bidirectionalbrushless direct current (BLDC) motor axial displacementhydraulic piston pump acting doubly as a double rodhydraulic cylinder accumulator check valves and reliefvalves The accumulator serves as a hydraulic reservoir pres-surizing to obtain improved response speed by increasingthe suction ability of the hydraulic pump and to preventcavitations of the EHA system The electric motor drivingthe hydraulic pump directly controls the hydraulic cylinderThe direction change of the hydraulic cylinder depends onthe change of rotation direction of the electric motor Alsoan electric motor installed in the EHA system controls theflow rate and pressure of the working fluid by controllingthe velocity and torque of the electric motor The DC powersupply which has a maximum DC power supply capacityof 27 kW supplies electric power to the electric motorThe detailed specifications of the components are shown inTable 1
In this paper we developed an EHA prototype which canbe used for various purposes in industries such as an aircraftactuation system mobile construction machinery servopress steering gear and injection molding machine with theoverall specifications shown in Table 2 Figure 1 is a photo ofthe position control test rig of the EHA system followed bythe schematic diagram of hydraulic position control test rigfor the developed EHA prototype in Figure 2
The test rig for the developed EHA prototype consists oftwo hydraulic cylinders amain cylinder which is a part of theEHA and a load cylinder Two cylinders are directly coupledby a shaft and the load mass is installed between the twocylinders The electric motor controls the main cylinder ofEHA while the load cylinder is controlled by the servo valve
The hydraulic flow to the main cylinder is controlled bythe electric BLDC servo motor operated through a driverdirectly connected to the proposed controller The positionof the main cylinder gets measured by a linear variabledisplacement transducer (LVDT) installed on the bracketattached to the load mass and another one is also installedin the hollow of the main cylinder rod The signal from theLVDT is used for the closed-loop control of themain cylindervia proposed controllers The output force gets measured bythe load cell installed at the coupling between two cylinders
The Scientific World Journal 3
Table 1 Specification of components for the EHA prototype
Specification ValuePump
Type Fixed displacement axial pistonpump (bidirectional)
Number of pistons 7Displacement 5 times 10
minus6m3
Maximum pressure 206 times 106 Pa
Motor
Type Brushless DC motorDC link voltage 270VRated current 524 ArmsRated torque 134NsdotmMax speed 10000 rpmPower 9 kW
Hydraulic cylinder
Type Double rod double actingPiston diameter 0108mDiameter of rod 0044mLength of stroke 00650mMaximum pressure 206 times 10
6 PaAccumulator
Acc Type BladderGas precharge pressure 049 times 10
6 PaAccumulator volume 07 L
Load massWeight 50 kg
DS1104 dSPACE board is used as a main control device toimplement proposed position controllers optimal PID opti-mal antiwindup PID controller and an adaptive antiwindupPID sliding mode controller The real-time control system isprogrammed by MATLABSimulink and gets transferred tothe dSPACE board through the Real-Time Workshop Theparameters of the controller implemented on the board can bechanged and monitored through the Control-Desk softwarein real time
3 Modeling of Position ControlSystem of EHA
In this section we derive a mathematical model of EHAsystems identifying system parameters by the signal com-pression method (SCM) in order to design the positioncontroller of EHA
31 Mathematical Model of EHA System Figure 3 shows theschematic diagram of EHA system As shown in Figure 3the pump inoutflows 119876
119886
119876119887
can be represented with the
Table 2 Specifications of the EHA prototype
Specifications ValuesStall force Max 1541NStroke Max plusmn337mmVelocity 1230sim1425mmsPower Max 90 kW
Servo valve and fiter
EHALoad cell
Load cylinder
Motor amplifier
Load mass
LVDT
Figure 1 Photo of the position control test rig of the EHA
pump inletoutlet chamber pressures 119901119886
119901119887
and the cylinderdisplacement 119909 as follows
119876119886
= 119863119901
120596119901
minus 120585 (119901119886
minus 119901119887
) minus119881119886
120573119890
119889119901119886
119889119905minus 119862119890119901
(119901119886
minus 119901119903
)
119876119887
= 119863119901
120596119901
minus 120585 (119901119886
minus 119901119887
) +119881119887
120573119890
119889119901119887
119889119905+ 119862119890119901
(119901119887
minus 119901119903
)
(1)
where 119863119901
is displacement of the pump 120585 is the pump crossport leakage coefficient 119862
119890119901
is the pump leakage coefficient119901119903
is the accumulator pressure 120573119890
stands for the effectivebulk modulus of the working fluid and119881
119886
119881119887
are inletoutletvolumes of pipe and cylinder chamber respectively
In addition the cylinder inletoutlet flows 1198761
1198762
can berepresented by
1198761
= 119860 +119881119886
120573119890
1198891199011
119889119905+ 119871 (119901
1
minus 1199012
)
1198762
= 119860 minus119881119887
120573119890
1198891199012
119889119905minus 119871 (119901
2
minus 1199011
)
(2)
where 119860 is pressurized area of hydraulic piston 119871 is internalleakage coefficient of the cylinder and 119901
1
1199012
are the cylinderinletoutlet chamber pressures respectively In this study theexternal leakage of the cylinder is neglected
In this study 119881119886
and 119881119887
are assumed to be equal dueto the double rod and double acting hydraulic cylinder isused in EHA system Also 119881
119886
and 119881119887
can be expressed with
4 The Scientific World Journal
Force
Reservoir
Position
M
Computer system
MATLAB Real-TimeWorkshop Simulink
Optimal PID controller
DS1104 dSPACE
Load cylinder
Main cylinder
Servo valve
Mass
Servo motordirver
Loadcontroller
LoadLVDT
AMP
cell
Figure 2 Schematic diagram for the test rig of the EHA prototype
Bidirectional variable displacement
axial piston pump
MassCylinder rod
Electricmotor
Piston
Cylinder
p1
Q1
p2
Q2
pa
Qa
pb
Qb
120596p
J
x
Figure 3 Schematic diagram of an EHA system
the nominal volume of each EHA chamber 1198810
which equalsthe mean volume of pipe and cylinder chamber as follows
119881119886
= 1198810
+ 119860119909
119881119887
= 1198810
minus 119860119909
(3)
Since a solid tubing is used in the prototype the pressureimpact of pipe expansion and flexibility on the effectivebulk modulus is assumed to be negligible Therefore therelationship pump port flows (119876
119886
119876119887
) and cylinder chamberflows (119876
1
1198762
) can be expressed as
1198761
= 119876119886
1198762
= 119876119887
(4)
Then the load 119876119871
can be defined as follows [21]
119876119871
=1198761
+ 1198762
2=119876119886
+ 119876119887
2 (5)
The relationship between the pump port pressures (119901119886
119901119887
) and cylinder chamber pressures (1199011
1199012
) can then beexpressed as
119901119886
= 1199011
+ 119901pipe
119901119887
= 1199012
minus 119901pipe(6)
where 119901pipe is pressure dropDue to the short length of tubing pump port pressures
are assumed to be equal that is the pressure drop can beneglected to the actuator inlet and outlet pressures such that[7 8 11 17 22]
119901119886
= 1199011
119901119887
= 1199012
(7)
Since the symmetrical double-rod hydraulic cylinder isused in this EHA system the following equation for thecylinder chamber pressures can be established
1198891199011
119889119905= minus
1198891199012
119889119905 (8)
By combining (1) (2) (5) (7) and (8) a simplifiedpumpcylinder model equation can be expressed as
119863119901
120596119901
= 119860 +1198810
120573119890
119871
+ 119862119879
119901119871
+ 1198911
(9)
where 119901119871
= 1199011
minus 1199012
119862119879
= 120585 + 119871 + (119862119901
2) is theequivalent leakage coefficient and 119891
1
is unmodeled dynamicsof hydraulic part of the EHA system
The actuator force and the displacement of the load canbe represented as
119865 = 119901119871
119860 = 119872 + 119861 + 1198912
(10)
The Scientific World Journal 5
where 119860 is pressurized area of hydraulic cylinder119872 is massof load 119861 is viscous friction coefficient and 119891
2
is lumpeduncertain nonlinearities due to external disturbance theunmodeled friction forces and other hard-to-model terms ofmechanical part of the EHA system
By combining (9) and (10) and neglecting 1198911
and 1198912
the linear transfer function between the angular velocity ofthe pump and the displacement of the main cylinder can beexpressed as
119866ℎ
(119904) =119909 (119904)
120596119901
(119904)
= (
119860119863119901
120573119890
1198721198810
)(1199043
+ (119861
119872+
119862119879
119863119901
120573119890
1198810
) 1199042
+
120573119890
(119861119862119879
119863119901
+ 1198602
)
1198721198810
119904)
minus1
(11)
where 119904 is the Laplace operatorBased on (11) the variation of the effective bulk modulus
of the working fluid can increase or decrease the compress-ibility of the working fluid and then the natural frequency ofthe EHA system can be adjusted meaning that the variationof the system parameters can affect the performance of theEHA position control system
On the other hand the dynamics of the BLDC motorwith controller that is electric part of the EHA system isconsidered as [14 23]
119866119898
(119904) =
120596119901
(119904)
V119903
(119904)=
119870119898
(1198791
119904 + 1)
119879119898
1
1199042
+ 119879119898
2
119904 + 1 (12)
where 119870119898
1198791
119879119898
1
and 119879119898
2
are parameters of the BLDCmotor with controller
32 Parameter Identification In general the unknown sys-tem parameters of the linear elements in a nonlinear systemcan be identified by the signal compression method (SCM)[24] In this study SCM is applied to identify the hydraulicpart of the EHA prototype
However hydraulic servo systems engage in significantnonlinear behavior due to system uncertainties such as pipelosses leakages and parameter variations of theworking fluid[9ndash11 16 17 19] Some of those uncertainties are sometimesneglected because the SCM can only identify the linear partof the system in the identification process This study thencompensates for the neglected nonlinear behavior of the EHAsystem by using a robust controller that is adaptive PIDsliding mode control scheme
As shown in Figure 4 the test signal that has the sameamplitude up to 4Hz in the frequency domain is applied tothe position control system of EHA by constructing a close-loop proportional control system to obtain a more accurateequivalent impulse response for the precise identification ofunknown parameters Figure 5 shows the comparison of thefrequency response of the position control system between
0 1 2 3 4 5 6 7 8minus3
minus25minus2
minus15minus1
minus050
051
152
253
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Figure 4 Test signal
40
50
60
70
ExperimentModel
Mag
nitu
de (d
B)
Frequency (Hz)10minus1 100 101
Figure 5 Bode plots of the closed loop nominal model and theclosed loop actual system with a proportional controller
the closed-loop nominal model and the closed-loop actualsystem with a proportional controller whose gain is 1000
The identified transfer function of a closed-loop actualsystem with a proportional controller for EHA positioncontrol system is as follows
119870119866 (119904)
1 + 119870119866 (119904)=
118 times 107
1199043
+ 22311199042
+ 718 times 105
119904 + 118 times 107
(13)
where119870 is proportional gain of closed-loop actual systemFrom the identified nominal model for the closed-loop
position control system for EHA with the proportionalcontroller the parameters of the position control system canbe acquired by eliminating the effect of the proportionalcontroller mathematically
6 The Scientific World Journal
0 1 2 3 4 5 6 7 8minus3
minus25minus2
minus15minus1
minus050
051
152
253
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
ExperimentModel
(a) Response for the test signal
0 05 1 15 2 25 3 35 4 45
0
2
4
6
8
10
12
14
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
minus2
ExperimentModel
(b) Step response
Figure 6 Time responses of the position control system obtained by the experiment and nominal model
After eliminating the effect of the proportional controllerthe identified transfer function of the hydraulic part of theEHA prototype is as follows
119866 (119904) =118 times 10
4
1199043
+ 22311199042
+ 718 times 105
119904 (14)
The identified system parameters were verified on thetime domain Figures 6(a) and 6(b) show the responseagainst test signal and the step responses of the nominalmodel and actual system respectively The validations ofthe identified parameters are estimated quantitatively by thecross-correlation as shown in [24]
Corr =sum119873
119896=1
(119884119901
(119896) minus 119884119901
) (119884119898
(119896) minus 119884119898
)
radicsum119873
119896=1
(119884119901
(119896) minus 119884119901
)radicsum119873
119896=1
(119884119898
(119896) minus 119884119898
)2
(15)
where 119884119901
(119896) and 119884119898
(119896) are the responses of the real andnominal model in time train 119896 respectively 119884
119901
and 119884119898
arethe mean values of 119884
119901
(119896) and 119884119898
(119896) 119873 is the acquired datanumberThe value of the cross-correlation is 0904 which canbe calculated from the identification results The identifiedsystem parameters are then available to controller designThe identified transfer function in (14) is used to obtain theoptimal control gains for designed position controllers byusing MATLABSimulink
In addition the dynamics characteristic of the BLDCmotor with controller is also investigated by using SCMThetransfer function of the BLDC motor with controller can besimplified to a second-order linear system as described in(12) Figure 7 shows bode plot of the actual BLDC motorwith controllerThe bandwidth of the actual open loop BLDCmotor with controller is about 400 rads The bandwidth ofthe BLDC motor with controller is 20 times larger than thatof hydraulic part of the EHA systemTherefore in this study
110
115
120
125
Experiment
Mag
nitu
de (d
B)
Frequency (Hz)100 101 102
Figure 7 Bode plots of the open-loop actual BLDC motor withcontroller system
we consider that the dynamics of BLDCmotorwith controlleris negligible because the motor dynamic is sufficiently fasterthan hydraulic part of the EHA Then the electric part ofthe EHA system is taking account of the motor gain 119870V andcurrent saturation is reflected in the controller design and thecomputer simulations stage
4 Position Controller Design fora Prototype EHA
In this study an EHA prototype is developed for appli-cation in the industrial fields As mentioned in Section 2performance characteristics such as no overshoot and rapidresponse time in position control are the typical demandsof the EHA for industrial use Therefore appropriate control
The Scientific World Journal 7
Positioncontroller
BLDC motor with controller
Hydraulic part of EHA system
Motorcontroller
r e
120596
e xi
Ks
Km
Tm 120596p
plusmn100A
minus+ minus+
rpmplusmn10000Reference position (xd) 1
Jms + Bm
x(s)
120596p(s)=
ADp120573e
e
MV0
s3 + ((BM) + (CTDp120573eV0))s2 + (120573 (BCTDp + A2)MV0)s
Figure 8 Block diagram for the position control system of the EHA
strategy should be applied to EHA position control system inorder to achieve these outcomes
Figure 8 shows the block diagram of position controlsystem of the EHA As mentioned in the previous section inFigure 8 the dynamics of the BLDC motor with controlleris considered as just the motor gain 119870
119898
and saturation ofcurrent of the BLDC motor is considered as an actuatorconstraint
In order to compare and show the desirable performancecharacteristics for the proposed EHA control system threekinds of position controllers are designed based on identifiedsimple transfer function First an optimal PID controller isdesigned and applied to the system in order to understandthe basic characteristics of EHA position control systemThe optimal antiwindup PID controller is then designed toreduce overshoot due to saturation of current in the electricmotor Finally an adaptive antiwindup PID sliding modecontroller is designed to obtain the desirable performanceand robustness against the effect of hardware saturation loaddisturbance and parameter variation
41 Optimal PID and Optimal Antiwindup PID ControlSystems An optimal PID position control system is designedto understand basic control performance of EHA prototypeAlso an optimal antiwindup PID control system for the EHAis designed to obtain desirable performance characteristicconsidering saturation in electric motor
The cost function is considered during the design ofthe optimal PID and optimal antiwindup PID controllers asfollows [25]
119869 (119870119901
119870119894
119870119889
) =
infin
sum
119905=0
(119910step (119905) minus 119910119889
step (119905)) (16)
where 119910119889step(119905) is the desired step response of the optimalPID and optimal antiwindup PID control systems and 119910step(119905)is the step response by the identified transfer function in(14)The optimal PID and optimal antiwindup PID controllerdesigns can be stated as
min119870
119901119870
119894119870
119889
119869 (119870119901
119870119894
119870119889
) (17)
where 119870119901
119870119894
and 119870119889
are the proportional integral anddifferential control gains respectively
There are many optimization algorithms in the opti-mization toolbox of MATLABSimulink The cost functionis given by (119870
119901
119870119894
119870119889
) And the gains of the optimal PIDand optimal antiwindup PID controllers 119870
119901
119870119894
and 119870119889
can be found by using the optimization toolbox of MAT-LABSimulink To find optimal control gains the referencestep input is applied in optimization process and the responseperformance is set as follows The amplitude of reference is20mm the rising time is 04 seconds settling time is 08seconds percent overshoot is under 5 and steady-stateerror is under 01mm
In the optimization process of optimal PID and optimalantiwindup PID controllers system parameter uncertaintiesdue to the modeling error are considered Specifically plusmn10ofmodeling error is considered in terms of identified transferfunction associate with variable system parameters such aseffective bulk modulus of the working fluid and total leakagecoefficient
With respect to optimal antiwindup PID and antiwindupPID sliding mode controllers the antiwindup algorithmshown in Figure 9 is used to consider saturation in an electricmotor [2 26ndash28]
Figure 10 shows the results of a computer simulationwith optimal antiwindup PID control gains using MAT-LABSimulink optimization toolbox based on identifiedtransfer function considering model uncertainty The dottedline there shows upper bound and lower bound consideringthe plusmn10 of modeling error and straight line shows nominalsimulation result with optimal antiwindup PID control gainsAs shown in Figure 10 the simulation result with optimalgains satisfies set response performance
42 Adaptive Antiwindup SlidingModeController Consideringthe PID Sliding Surface In this study the adaptive anti-windup PID sliding mode control scheme is also designedto achieve desirable performance and robustness of EHAposition control systems Throughout the controller designprocess the effective bulk modulus and leakage coefficientsare considered as variable systemparameters In order to con-sider saturation in electric motor the antiwindup algorithmpresented in Figure 8 also applies to the adaptive antiwindupPID sliding mode control scheme
8 The Scientific World Journal
Position controller BLDC motor with controller
Motorcontroller
r i re
120596
i
Ks
Ks Km
Tm
plusmn100A
minus+
+++
+
rpmplusmn10000
minus
ka
ei
s
k2s
orKi
s
k3 or Kd
k1 or Kpe 120596p1
Jms + Bm
Figure 9 Block diagram for adopted antiwindup algorithm in controller design
06 07 08 09 1 1118
19
20
21
22Upper boundary
Lower boundary
Nominal response
0 02 04 06 08 1 12 14 16 18 20
5
10
15
20
25
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
Figure 10 Step response of the optimal antiwindup PID controlsystem in computer simulation based on identified transfer functionof EHA system
The PID sliding surface 120577 for the design of the adaptivesliding mode control system is defined as [29ndash32]
120577 = 1198961
119890 + 1198962
int 119890 119889119905 + 1198963
119890 (18)
where the tracking error of the position 119890 = 119909119889
minus 119909 119909 isthe displacement of hydraulic cylinder and 119896
1
1198962
and 1198963
arepositive design parameters
The sliding mode control law consists of equivalent androbust control term that is
120596119901
= 120596119901119890119902
+ 120596119901robust (19)
By combining (11) and (18) with consideration of the noiseterm in the jerk =
119898
+ 119899
the derivative of the slidingsurface 120577 can be written as
120577 = minus 1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
120596119901
+ 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119898
+ 119899
)
+ 1198963
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+ 1198963
119889
+ 1198961
119890 + 1198962
119890
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891
(20)
where 119891 = 1198911
+ (119862119879
119860)1198912
+ (1198810
119860119863119901
120573119890
) 1198912
is lumped uncer-tain nonlinearities of the EHA system and the subscripts 119898and 119899 denote the nominal and noisy values respectively
To determine the equivalent control term 120596119901119890119902
the noiseterm in the jerk is neglected and it is assumed that the slidingsurface 120577 is at steady-state that is 120577 = 0 and then theequivalent control law can be determined as
120596119901119890119902
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119889
(21)
Thus 120577 can be rewritten as
120577 = 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119899
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891 (22)
In the standard sliding mode control to satisfy the reach-ability condition that directs system trajectories toward asliding surface where they remain and to attenuate chatteringin the control input the derivative of the sliding surface isselected as [33 34]
120577 = minus119863120577 minus 119870 sgn (120577) (23)
where119863 and119870 are positive design parameters
The Scientific World Journal 9
To determine a robust control term120596119901robust that achieves
robustness to uncertainties such as noise terms in the jerk andunmodeled system dynamics as well as the disturbance forceit is assumed that
1198630
10038161003816100381610038161205771003816100381610038161003816 + 1198700 gt
100381610038161003816100381610038161003816100381610038161003816
1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119899
+1
1198721198810
119891)
100381610038161003816100381610038161003816100381610038161003816
+ 120578
(24)
where 1198700
= (119860119863119901
120573119890
(1198611198810
+ 119862119879
119863119901
119872120573119890
))119870 and 1198630
=
(119860119863119901
120573119890
(1198611198810
+119862119879
119863119901
119872120573119890
))119863 are positive design parametersand 120578 is sufficiently small positive parameter On the assump-tion of (24) the robust control law is determined as
120596119901robust = 119863120577 + 119870 sgn (120577) (25)
Finally the sliding mode control law is selected as
120596119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 119889
+1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119863120577 + 119870 sgn (120577)
(26)
If the total leakage coefficient 119862119879
and the effective bulkmodulus of EHA systems 120573
119890
are considered as variableparameters that is 119862
119879
= 119862119879119899
+ 119862119879119901
and 120573119890
= 120573119890119899
+ 120573119890119901
then the uncertainty 120595 is defined as
120595 = 120579119879
120593 = (1198721198810
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
) 119898
+ (
(1198602
+ 119861119862119879119901
119863119901
) 120573119890119901
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)
(27)
where 120579119879
= [(1198721198810
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)) ((1198602
+
119861119862119879119901
119863119901
)120573119890119901
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
))] and 120593 = [119909
119898
119909
] Theparameter vector 120579 is considered as an unknown parametervector and it can be estimated by using the update lawFrom (26) and estimated unknown parameter vector 120579 theestimated sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119860119863119901
120573119890119899
times 119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
+ 119863120577 + 119870 sgn (120577)
(28)
In order to obtain the update law for the unknownparameters the Lyapunov candidate is defined as
119881 =1
21205772
+1
2120574120579119879
120579 (29)
where 120579 = 120579 minus 120579 120574 is a positive parameter Also 120579 and 120579 arethe nominal and estimated parameter vectors respectivelyThe derivative of the Lyapunov candidate including slidingdynamics is expressed as
= 120577 [119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
minus1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
119901
] minus1
120574120579119879120579
(30)
Substituting the estimated angular velocity of the pump 119901
given by (28) into (30) yields
= minus1198631205772
minus 119870120577 sgn (120577) + 120579119879 (120577120593 minus 1120574
120579) (31)
From the derivative of the Lyapunov included sliding dynam-ics the update law for the unknown parameters is selected as
120579 = 120574120577120593 (32)
Therefore the derivative of the Lyapunov is given as
= minus1198631205772
minus 119870120577 sgn (120577) le 0 (33)
By applying invariant set theorem for (33) the asymptoticalstability of the EHAposition control system is guaranteed [3334]
Finally the sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times (120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890)
+ 119863120577 + 119870 sgn (120577) (34)
where 120573119890
(119905 + 119879119904
) = (119889120573119890
(119905)119889119905)119879119904
+ 120573119890
(119905) 119862119879
(119905 + 119879119904
) =
(119889119862119879
(119905)119889119905)119879119904
+ 119862119879
(119905) and 119879119904
is the sampling time
10 The Scientific World Journal
Table 3 Optimal gains of optimal PID antiwindup PID and adaptive anti-windup PID sliding mode control systems in experiments
Gain Optimal PID Optimal antiwindup PID Adaptive antiwindup PID sliding modeProportional (119870
119901
or 1198961
) 10343 16947 950Integral (119870
119894
or 1198962
) 184 10877 0001Derivative (119870
119889
or 1198963
) 47 4160 145Antiwindup (119870
119886
) mdash 0001 0001
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 11 Performances of optimal PID position control system for EHA without load disturbance (only mass load is applied)
5 Experimental Results and Discussion
This section looks to the experimental results in order tocompare the performance of a position control systemsThreekinds of controllers are compared in order to show improvedperformance of overshoot reduction and robustness to theparameter change and load disturbance of the proposedcontroller for EHA position control system
Firstly optimal PID controller is designed and imple-mented by experiments Figure 11 shows experimental resultsof the PID position controller with step references of fourdifferent amplitudes which are 10 20 30 and 40mmwithoutload disturbance that is only mass load is applied as load tothe position control system
The gains of the three-position controllers are optimallyselected by using MATLABSimulink optimization toolboxbased on identified system dynamic model of (14) In theprocess of optimal gain selection the amplitude of positionreference is set to 20mm and target performance is 04seconds of the rising time 08 seconds of settling timeunder 5 of percent overshoot and under 01mm of steady-state error In experiments the optimal gains derived fromMATLABSimulink optimization toolbox are tuned to obtainbest responses The finally tuned optimal gains of the threecontrollers are represented in Table 3
As shown in Figure 11 large overshoot is observed inposition control result for using the optimal PID positioncontroller The performance of optimal PID position control
system is represented in Table 4The performance of optimalPID controller in experiment is not satisfactory the aimedvalue In detail large overshoot is observed in experimentsThe current and angular velocity saturations of BLDC motorin position experiment result of optimal PID controller areshown in Figure 12The large overshoot in position controllercan be caused due to saturation of BLDC motor as shown inFigure 12
To reduce such a large overshoot an antiwindup algo-rithmwhich is described in Figure 9 is applied to the positioncontrol system of the EHA The performance characteristicsof an antiwindup PID position controller are depicted inFigure 13 and also the values of performance indices areshown in Table 4 As shown in Figure 13 the overshoot ofthe optimal antiwindup PID controller is more diminishedthan that of the optimal PID controller However as shown inTable 4 the antiwindupPID controller still has a performanceof relatively long settling times which do not meet the aimedperformance Moreover as the amplitude of the referenceinput increases the steady-state error is increasing as shownin Figure 13
Figure 14 shows the experimental results of optimal adap-tive antiwindup sliding mode position control system for theEHA system As shown in Figure 14 the optimal antiwindupPID sliding mode position control system has a better per-formance than the system with optimal PID and antiwindupPID controllers such that relatively small overshoot and shortsettling time are obtained by the adaptive antiwindup PID
The Scientific World Journal 11
Table 4 Comparison of the performance of optimal PID optimal antiwindup PID and adaptive antiwindup PID sliding mode controlsystems without load disturbance
Performance Reference Optimal PID Optimal antiwindup PID Adaptive antiwindup PIDsliding mode
Overshoot
10mm 389 208 1020mm 161 133 0530mm 147 119 0240mm 122 82 01
Settling time
10mm 178 sec 22 sec 06 sec20mm 056 sec 22 sec 06 sec30mm 058 sec 063 sec 07 sec40mm 069 sec 26 sec 07 sec
0 05 1 15 2 25 3minus120
minus90
minus60
minus30
0
30
60
90
120
150
Impr
esse
d cu
rren
t (A
)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(a) Saturation of impressed current
0 05 1 15 2 25 3minus6000
minus4000
minus2000
0
2000
4000
6000
8000
10000
12000
14000
Mot
or an
gula
r spe
ed (r
pm)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Saturation of angular velocity
Figure 12 Saturation of BLDCmotor for optimal PID position control system for EHAwithout load disturbance (only mass load is applied)
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 13 Performances of optimal antiwindup PID position control system for EHA without load disturbance (only mass load is applied)
12 The Scientific World Journal
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 14 Performances of optimal adaptive antiwindup PID sliding mode position control system for EHA without load disturbance (onlymass load is applied)
0 05 1 15 2 25 30
1
2
3
4
5
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 15 Pressure variations of optimal PID position control system for EHA without load disturbance (only mass load is applied)
sliding mode control system As shown in Figure 14 andTable 4 the consistent performance is realized by the optimaladaptive antiwindup PID sliding mode control system Thetime-domain quantitative performance indicators are alsosummarized in Table 4 for optimal adaptive antiwindup PIDsliding mode control system without load
On the other hand Figure 15 depicts pressure variationsof the optimal PID EHAposition control systemwithout loaddisturbance As shown in Figure 15 the range of operatingpressure of the EHA system is under 3MPa inwhich the effec-tive bulk modulus can be significantly changed according tocontained air ratio of working fluid [5 7 11ndash13] as shownin Figure 16 The range of operating pressure for antiwindup
PID and antiwindup PID sliding mode control system is alsounder 3MPa
Figure 17 depicts pressures of the EHA system when theposition control systems are operating with load disturbanceAs shown in Figure 17 the maximum operating pressures ofthe EHA system is about 10MPa when the position controlsystems are working under the condition of adding distur-bance loadThemaximumoperating pressure for antiwindupPID and antiwindup PID sliding mode control system isalso up to 10MPa Thus the effective bulk modulus can bechanged greatly according to variation of operating pressureof the EHA systems In addition total leakage coefficient alsocan be changed in response to the level of working pressure
The Scientific World Journal 13
0 5 10 15 20 25 300
400
800
1200
1600
2000
Bulk
mod
ulus
(MPa
)
Pressure (MPa)
Contained air ratio ()001
110
Figure 16 Example of the relationship between pressure and effective bulk modulus [12 13]
0 05 1 15 2 25 30123456789
101112
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 17 Pressure variations of optimal PID position control system for EHA with load disturbance
In order to investigate robustness to the lumped systemuncertainties such as varying parameters and modeling errorand load disturbance the performances of the three-positioncontrollers of EHA system are compared in experiments byapplying load disturbance The experiments are conductedwith 20mm position reference and the load disturbance isapplied by controlling the opening area of servo valve whichis installed in a meter outline of load cylinder
As shown in Figure 18 the optimal PID and optimalantiwindup PID control systems do not achieve robustnessto the parameter change and load disturbance In spite of theload disturbance and saturation of the BLDC motor in theposition control system for EHA the adaptive antiwindupPID sliding mode control system has a better performanceand robustness than the optimal PID and optimal antiwindupPID control systems such that the adaptive antiwindup PID
sliding mode control system recovers the parameter changeand external disturbance in about 09 sec with a small over-shootThe time-domain quantitative performance indicatorsare summarized in Table 5 for optimal PID antiwindup PIDand adaptive antiwindup PID sliding mode control systemswith load disturbance The list of terms are represented inTable 6
6 Conclusion
This paper discussed the application of the optimal PIDcontroller with optimal control gains using the optimizationtoolbox ofMATLABSimulink to the position control systemof EHA in order to understand the basic performancecharacteristics of the system In experiment with optimal PIDcontroller large overshoot due to saturation of electric motoris observed
14 The Scientific World Journal
0 05 1 15 2 25 30
5
10
15
20
25
30
35
Position referenceOptimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(b) Position errors
0 05 1 15 2 25 30
2
4
6
8
10
Load
forc
e (kN
)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(c) Load force
Figure 18 Performances of optimal PID antiwindup PID and adaptive antiwindup PID sliding mode control systems for EHA with loaddisturbance
Table 5 Comparison of the performance of optimal PID optimalantiwindup PID and adaptive antiwindup PID slidingmode controlsystems with load disturbance
Performance OptimalPID
Optimalantiwindup PID
Adaptive antiwindupPID sliding mode
Overshoot 45 39 12Settling time 38 sec 18 sec 08 sec
In order to achieve the desirable performance of EHAposition control system optimal antiwindup PID controller
and adaptive antiwindup PID sliding mode controller arealso applied to control the position of EHA systems Inthe process of robust control system design mathematicalmodeling was carried out based on theoretical analysisand the simple third-order nominal model was derivedThe system parameters of the simple second-order nominalmodel were identified by the signal compression method
Based on the experimental results and the time-domainquantitative performance indicators the performance of theEHA position control system can be improved and robustto the load disturbance parameter variation and system
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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![Page 2: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/2.jpg)
2 The Scientific World Journal
which can use relatively little working fluidThe performanceof the EHA system can also be sensitive to variation withinthe system parameters of the working fluid such as varietyof effective bulk modulus and the leakage coefficient due tochanges in the working environment [5 7 9 11ndash13] Thosenonlinearity and uncertainty may cause the position controlsystem of the EHA to be unstable or have a much degradedperformance
In order to obtain the desirable performance of an EHAposition control system a number of control strategies havebeen applied and investigated by many researchers Some ofthe work has used linear control theory for the position con-trol of EHA [14ndash16] The nonlinear robust control schemessuch as sliding mode control back-stepping control andFuzzy logic control have been proposed to achieve robustnessof position control system for EHA by compensating systemnonlinearity and uncertainties and to compensate for thenonlinear dynamics of EHA system such as friction [3 5 6 9ndash11 14 17 18] Adaptive control approaches have been also pro-posed to make up for parameter disturbances such as varyingthe viscous friction coefficient and the effective bulkmodulusdue to change of working condition [1ndash3 9 11 19 20]
However a fast response with small overshoot should bethe objective for the practical use of the EHA position controlsystems in industrial machine such as plastic injection mold-ing machine aircraft actuation system mobile machineryCNC pipe bending machines and hydraulic servo controlof steering system for ship and hydraulic press [1 2] eventhough there are lots of uncertainties and nonlinearity inposition control system of EHA The problem concerninglarge overshoot from the saturation in the electric motor hasbeen considered in recent studies [2] In [2] the saturationof voltage and current of the PWM driver and DC poweris taken into account for position control system of EHAThe researchers of [2] also consider dead zone torque due tothe static friction of motor pump and variable load torqueThe PD-PI hybrid control scheme is proposed to controlthe BLDC motor in order to achieve small overshoot andto compensate for the load disturbances However only acomputer simulation can verify the proposed linear controlscheme although there are lots of uncertainty and nonlinear-ity besides the dead zone and motor saturation In [2 19]they proposed a self-turning Fuzzy PID control scheme tocompensate for the dead zone saturation of motor angularvelocity parameter uncertainties and load disturbance withexperimental verification However improved accuracy andfast response appear necessary to apply the position controlresults to servo press Also the design of fuzzy rules dependslargely on the experience of experts or input-output data
In this research an adaptive antiwindup PID slidingmode control scheme is proposed to solve problems ofovershoot in position control caused by saturation of angu-lar velocity to the electric motor The previous researchesconsidered an antiwindup scheme based on the conventionalsliding mode controller [21 22] However the proposedcontroller consists of an adaptive control and a conventionalsliding mode control with antiwindup scheme Thereforethe proposed control scheme looks to implement robustnessto parameter variations in a variety of working condition
nonlinearity and load disturbance The validation of theproposed control scheme is verified by experiment
This paper will proceed as follows Section 2 reveals thecomposition and details of the position control test rig of anEHA prototype followed by systemmodeling and parameteridentification of the EHA systems in Section 3 In Section 4position controllers for the EHA system using traditionalPID antiwindup PID and adaptive antiwindup PID slidingmode control schemes are presentedThe comparative resultsof the experimental tests executed on the position controltest rig of EHA applying PID antiwindup PID and adaptiveantiwindup PID sliding mode control schemes are revealedin Section 5 followed by conclusions in Section 6
2 Experimental Setup of the ElectrohydraulicActuator Prototype
In this study the EHA system consists of a bidirectionalbrushless direct current (BLDC) motor axial displacementhydraulic piston pump acting doubly as a double rodhydraulic cylinder accumulator check valves and reliefvalves The accumulator serves as a hydraulic reservoir pres-surizing to obtain improved response speed by increasingthe suction ability of the hydraulic pump and to preventcavitations of the EHA system The electric motor drivingthe hydraulic pump directly controls the hydraulic cylinderThe direction change of the hydraulic cylinder depends onthe change of rotation direction of the electric motor Alsoan electric motor installed in the EHA system controls theflow rate and pressure of the working fluid by controllingthe velocity and torque of the electric motor The DC powersupply which has a maximum DC power supply capacityof 27 kW supplies electric power to the electric motorThe detailed specifications of the components are shown inTable 1
In this paper we developed an EHA prototype which canbe used for various purposes in industries such as an aircraftactuation system mobile construction machinery servopress steering gear and injection molding machine with theoverall specifications shown in Table 2 Figure 1 is a photo ofthe position control test rig of the EHA system followed bythe schematic diagram of hydraulic position control test rigfor the developed EHA prototype in Figure 2
The test rig for the developed EHA prototype consists oftwo hydraulic cylinders amain cylinder which is a part of theEHA and a load cylinder Two cylinders are directly coupledby a shaft and the load mass is installed between the twocylinders The electric motor controls the main cylinder ofEHA while the load cylinder is controlled by the servo valve
The hydraulic flow to the main cylinder is controlled bythe electric BLDC servo motor operated through a driverdirectly connected to the proposed controller The positionof the main cylinder gets measured by a linear variabledisplacement transducer (LVDT) installed on the bracketattached to the load mass and another one is also installedin the hollow of the main cylinder rod The signal from theLVDT is used for the closed-loop control of themain cylindervia proposed controllers The output force gets measured bythe load cell installed at the coupling between two cylinders
The Scientific World Journal 3
Table 1 Specification of components for the EHA prototype
Specification ValuePump
Type Fixed displacement axial pistonpump (bidirectional)
Number of pistons 7Displacement 5 times 10
minus6m3
Maximum pressure 206 times 106 Pa
Motor
Type Brushless DC motorDC link voltage 270VRated current 524 ArmsRated torque 134NsdotmMax speed 10000 rpmPower 9 kW
Hydraulic cylinder
Type Double rod double actingPiston diameter 0108mDiameter of rod 0044mLength of stroke 00650mMaximum pressure 206 times 10
6 PaAccumulator
Acc Type BladderGas precharge pressure 049 times 10
6 PaAccumulator volume 07 L
Load massWeight 50 kg
DS1104 dSPACE board is used as a main control device toimplement proposed position controllers optimal PID opti-mal antiwindup PID controller and an adaptive antiwindupPID sliding mode controller The real-time control system isprogrammed by MATLABSimulink and gets transferred tothe dSPACE board through the Real-Time Workshop Theparameters of the controller implemented on the board can bechanged and monitored through the Control-Desk softwarein real time
3 Modeling of Position ControlSystem of EHA
In this section we derive a mathematical model of EHAsystems identifying system parameters by the signal com-pression method (SCM) in order to design the positioncontroller of EHA
31 Mathematical Model of EHA System Figure 3 shows theschematic diagram of EHA system As shown in Figure 3the pump inoutflows 119876
119886
119876119887
can be represented with the
Table 2 Specifications of the EHA prototype
Specifications ValuesStall force Max 1541NStroke Max plusmn337mmVelocity 1230sim1425mmsPower Max 90 kW
Servo valve and fiter
EHALoad cell
Load cylinder
Motor amplifier
Load mass
LVDT
Figure 1 Photo of the position control test rig of the EHA
pump inletoutlet chamber pressures 119901119886
119901119887
and the cylinderdisplacement 119909 as follows
119876119886
= 119863119901
120596119901
minus 120585 (119901119886
minus 119901119887
) minus119881119886
120573119890
119889119901119886
119889119905minus 119862119890119901
(119901119886
minus 119901119903
)
119876119887
= 119863119901
120596119901
minus 120585 (119901119886
minus 119901119887
) +119881119887
120573119890
119889119901119887
119889119905+ 119862119890119901
(119901119887
minus 119901119903
)
(1)
where 119863119901
is displacement of the pump 120585 is the pump crossport leakage coefficient 119862
119890119901
is the pump leakage coefficient119901119903
is the accumulator pressure 120573119890
stands for the effectivebulk modulus of the working fluid and119881
119886
119881119887
are inletoutletvolumes of pipe and cylinder chamber respectively
In addition the cylinder inletoutlet flows 1198761
1198762
can berepresented by
1198761
= 119860 +119881119886
120573119890
1198891199011
119889119905+ 119871 (119901
1
minus 1199012
)
1198762
= 119860 minus119881119887
120573119890
1198891199012
119889119905minus 119871 (119901
2
minus 1199011
)
(2)
where 119860 is pressurized area of hydraulic piston 119871 is internalleakage coefficient of the cylinder and 119901
1
1199012
are the cylinderinletoutlet chamber pressures respectively In this study theexternal leakage of the cylinder is neglected
In this study 119881119886
and 119881119887
are assumed to be equal dueto the double rod and double acting hydraulic cylinder isused in EHA system Also 119881
119886
and 119881119887
can be expressed with
4 The Scientific World Journal
Force
Reservoir
Position
M
Computer system
MATLAB Real-TimeWorkshop Simulink
Optimal PID controller
DS1104 dSPACE
Load cylinder
Main cylinder
Servo valve
Mass
Servo motordirver
Loadcontroller
LoadLVDT
AMP
cell
Figure 2 Schematic diagram for the test rig of the EHA prototype
Bidirectional variable displacement
axial piston pump
MassCylinder rod
Electricmotor
Piston
Cylinder
p1
Q1
p2
Q2
pa
Qa
pb
Qb
120596p
J
x
Figure 3 Schematic diagram of an EHA system
the nominal volume of each EHA chamber 1198810
which equalsthe mean volume of pipe and cylinder chamber as follows
119881119886
= 1198810
+ 119860119909
119881119887
= 1198810
minus 119860119909
(3)
Since a solid tubing is used in the prototype the pressureimpact of pipe expansion and flexibility on the effectivebulk modulus is assumed to be negligible Therefore therelationship pump port flows (119876
119886
119876119887
) and cylinder chamberflows (119876
1
1198762
) can be expressed as
1198761
= 119876119886
1198762
= 119876119887
(4)
Then the load 119876119871
can be defined as follows [21]
119876119871
=1198761
+ 1198762
2=119876119886
+ 119876119887
2 (5)
The relationship between the pump port pressures (119901119886
119901119887
) and cylinder chamber pressures (1199011
1199012
) can then beexpressed as
119901119886
= 1199011
+ 119901pipe
119901119887
= 1199012
minus 119901pipe(6)
where 119901pipe is pressure dropDue to the short length of tubing pump port pressures
are assumed to be equal that is the pressure drop can beneglected to the actuator inlet and outlet pressures such that[7 8 11 17 22]
119901119886
= 1199011
119901119887
= 1199012
(7)
Since the symmetrical double-rod hydraulic cylinder isused in this EHA system the following equation for thecylinder chamber pressures can be established
1198891199011
119889119905= minus
1198891199012
119889119905 (8)
By combining (1) (2) (5) (7) and (8) a simplifiedpumpcylinder model equation can be expressed as
119863119901
120596119901
= 119860 +1198810
120573119890
119871
+ 119862119879
119901119871
+ 1198911
(9)
where 119901119871
= 1199011
minus 1199012
119862119879
= 120585 + 119871 + (119862119901
2) is theequivalent leakage coefficient and 119891
1
is unmodeled dynamicsof hydraulic part of the EHA system
The actuator force and the displacement of the load canbe represented as
119865 = 119901119871
119860 = 119872 + 119861 + 1198912
(10)
The Scientific World Journal 5
where 119860 is pressurized area of hydraulic cylinder119872 is massof load 119861 is viscous friction coefficient and 119891
2
is lumpeduncertain nonlinearities due to external disturbance theunmodeled friction forces and other hard-to-model terms ofmechanical part of the EHA system
By combining (9) and (10) and neglecting 1198911
and 1198912
the linear transfer function between the angular velocity ofthe pump and the displacement of the main cylinder can beexpressed as
119866ℎ
(119904) =119909 (119904)
120596119901
(119904)
= (
119860119863119901
120573119890
1198721198810
)(1199043
+ (119861
119872+
119862119879
119863119901
120573119890
1198810
) 1199042
+
120573119890
(119861119862119879
119863119901
+ 1198602
)
1198721198810
119904)
minus1
(11)
where 119904 is the Laplace operatorBased on (11) the variation of the effective bulk modulus
of the working fluid can increase or decrease the compress-ibility of the working fluid and then the natural frequency ofthe EHA system can be adjusted meaning that the variationof the system parameters can affect the performance of theEHA position control system
On the other hand the dynamics of the BLDC motorwith controller that is electric part of the EHA system isconsidered as [14 23]
119866119898
(119904) =
120596119901
(119904)
V119903
(119904)=
119870119898
(1198791
119904 + 1)
119879119898
1
1199042
+ 119879119898
2
119904 + 1 (12)
where 119870119898
1198791
119879119898
1
and 119879119898
2
are parameters of the BLDCmotor with controller
32 Parameter Identification In general the unknown sys-tem parameters of the linear elements in a nonlinear systemcan be identified by the signal compression method (SCM)[24] In this study SCM is applied to identify the hydraulicpart of the EHA prototype
However hydraulic servo systems engage in significantnonlinear behavior due to system uncertainties such as pipelosses leakages and parameter variations of theworking fluid[9ndash11 16 17 19] Some of those uncertainties are sometimesneglected because the SCM can only identify the linear partof the system in the identification process This study thencompensates for the neglected nonlinear behavior of the EHAsystem by using a robust controller that is adaptive PIDsliding mode control scheme
As shown in Figure 4 the test signal that has the sameamplitude up to 4Hz in the frequency domain is applied tothe position control system of EHA by constructing a close-loop proportional control system to obtain a more accurateequivalent impulse response for the precise identification ofunknown parameters Figure 5 shows the comparison of thefrequency response of the position control system between
0 1 2 3 4 5 6 7 8minus3
minus25minus2
minus15minus1
minus050
051
152
253
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Figure 4 Test signal
40
50
60
70
ExperimentModel
Mag
nitu
de (d
B)
Frequency (Hz)10minus1 100 101
Figure 5 Bode plots of the closed loop nominal model and theclosed loop actual system with a proportional controller
the closed-loop nominal model and the closed-loop actualsystem with a proportional controller whose gain is 1000
The identified transfer function of a closed-loop actualsystem with a proportional controller for EHA positioncontrol system is as follows
119870119866 (119904)
1 + 119870119866 (119904)=
118 times 107
1199043
+ 22311199042
+ 718 times 105
119904 + 118 times 107
(13)
where119870 is proportional gain of closed-loop actual systemFrom the identified nominal model for the closed-loop
position control system for EHA with the proportionalcontroller the parameters of the position control system canbe acquired by eliminating the effect of the proportionalcontroller mathematically
6 The Scientific World Journal
0 1 2 3 4 5 6 7 8minus3
minus25minus2
minus15minus1
minus050
051
152
253
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
ExperimentModel
(a) Response for the test signal
0 05 1 15 2 25 3 35 4 45
0
2
4
6
8
10
12
14
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
minus2
ExperimentModel
(b) Step response
Figure 6 Time responses of the position control system obtained by the experiment and nominal model
After eliminating the effect of the proportional controllerthe identified transfer function of the hydraulic part of theEHA prototype is as follows
119866 (119904) =118 times 10
4
1199043
+ 22311199042
+ 718 times 105
119904 (14)
The identified system parameters were verified on thetime domain Figures 6(a) and 6(b) show the responseagainst test signal and the step responses of the nominalmodel and actual system respectively The validations ofthe identified parameters are estimated quantitatively by thecross-correlation as shown in [24]
Corr =sum119873
119896=1
(119884119901
(119896) minus 119884119901
) (119884119898
(119896) minus 119884119898
)
radicsum119873
119896=1
(119884119901
(119896) minus 119884119901
)radicsum119873
119896=1
(119884119898
(119896) minus 119884119898
)2
(15)
where 119884119901
(119896) and 119884119898
(119896) are the responses of the real andnominal model in time train 119896 respectively 119884
119901
and 119884119898
arethe mean values of 119884
119901
(119896) and 119884119898
(119896) 119873 is the acquired datanumberThe value of the cross-correlation is 0904 which canbe calculated from the identification results The identifiedsystem parameters are then available to controller designThe identified transfer function in (14) is used to obtain theoptimal control gains for designed position controllers byusing MATLABSimulink
In addition the dynamics characteristic of the BLDCmotor with controller is also investigated by using SCMThetransfer function of the BLDC motor with controller can besimplified to a second-order linear system as described in(12) Figure 7 shows bode plot of the actual BLDC motorwith controllerThe bandwidth of the actual open loop BLDCmotor with controller is about 400 rads The bandwidth ofthe BLDC motor with controller is 20 times larger than thatof hydraulic part of the EHA systemTherefore in this study
110
115
120
125
Experiment
Mag
nitu
de (d
B)
Frequency (Hz)100 101 102
Figure 7 Bode plots of the open-loop actual BLDC motor withcontroller system
we consider that the dynamics of BLDCmotorwith controlleris negligible because the motor dynamic is sufficiently fasterthan hydraulic part of the EHA Then the electric part ofthe EHA system is taking account of the motor gain 119870V andcurrent saturation is reflected in the controller design and thecomputer simulations stage
4 Position Controller Design fora Prototype EHA
In this study an EHA prototype is developed for appli-cation in the industrial fields As mentioned in Section 2performance characteristics such as no overshoot and rapidresponse time in position control are the typical demandsof the EHA for industrial use Therefore appropriate control
The Scientific World Journal 7
Positioncontroller
BLDC motor with controller
Hydraulic part of EHA system
Motorcontroller
r e
120596
e xi
Ks
Km
Tm 120596p
plusmn100A
minus+ minus+
rpmplusmn10000Reference position (xd) 1
Jms + Bm
x(s)
120596p(s)=
ADp120573e
e
MV0
s3 + ((BM) + (CTDp120573eV0))s2 + (120573 (BCTDp + A2)MV0)s
Figure 8 Block diagram for the position control system of the EHA
strategy should be applied to EHA position control system inorder to achieve these outcomes
Figure 8 shows the block diagram of position controlsystem of the EHA As mentioned in the previous section inFigure 8 the dynamics of the BLDC motor with controlleris considered as just the motor gain 119870
119898
and saturation ofcurrent of the BLDC motor is considered as an actuatorconstraint
In order to compare and show the desirable performancecharacteristics for the proposed EHA control system threekinds of position controllers are designed based on identifiedsimple transfer function First an optimal PID controller isdesigned and applied to the system in order to understandthe basic characteristics of EHA position control systemThe optimal antiwindup PID controller is then designed toreduce overshoot due to saturation of current in the electricmotor Finally an adaptive antiwindup PID sliding modecontroller is designed to obtain the desirable performanceand robustness against the effect of hardware saturation loaddisturbance and parameter variation
41 Optimal PID and Optimal Antiwindup PID ControlSystems An optimal PID position control system is designedto understand basic control performance of EHA prototypeAlso an optimal antiwindup PID control system for the EHAis designed to obtain desirable performance characteristicconsidering saturation in electric motor
The cost function is considered during the design ofthe optimal PID and optimal antiwindup PID controllers asfollows [25]
119869 (119870119901
119870119894
119870119889
) =
infin
sum
119905=0
(119910step (119905) minus 119910119889
step (119905)) (16)
where 119910119889step(119905) is the desired step response of the optimalPID and optimal antiwindup PID control systems and 119910step(119905)is the step response by the identified transfer function in(14)The optimal PID and optimal antiwindup PID controllerdesigns can be stated as
min119870
119901119870
119894119870
119889
119869 (119870119901
119870119894
119870119889
) (17)
where 119870119901
119870119894
and 119870119889
are the proportional integral anddifferential control gains respectively
There are many optimization algorithms in the opti-mization toolbox of MATLABSimulink The cost functionis given by (119870
119901
119870119894
119870119889
) And the gains of the optimal PIDand optimal antiwindup PID controllers 119870
119901
119870119894
and 119870119889
can be found by using the optimization toolbox of MAT-LABSimulink To find optimal control gains the referencestep input is applied in optimization process and the responseperformance is set as follows The amplitude of reference is20mm the rising time is 04 seconds settling time is 08seconds percent overshoot is under 5 and steady-stateerror is under 01mm
In the optimization process of optimal PID and optimalantiwindup PID controllers system parameter uncertaintiesdue to the modeling error are considered Specifically plusmn10ofmodeling error is considered in terms of identified transferfunction associate with variable system parameters such aseffective bulk modulus of the working fluid and total leakagecoefficient
With respect to optimal antiwindup PID and antiwindupPID sliding mode controllers the antiwindup algorithmshown in Figure 9 is used to consider saturation in an electricmotor [2 26ndash28]
Figure 10 shows the results of a computer simulationwith optimal antiwindup PID control gains using MAT-LABSimulink optimization toolbox based on identifiedtransfer function considering model uncertainty The dottedline there shows upper bound and lower bound consideringthe plusmn10 of modeling error and straight line shows nominalsimulation result with optimal antiwindup PID control gainsAs shown in Figure 10 the simulation result with optimalgains satisfies set response performance
42 Adaptive Antiwindup SlidingModeController Consideringthe PID Sliding Surface In this study the adaptive anti-windup PID sliding mode control scheme is also designedto achieve desirable performance and robustness of EHAposition control systems Throughout the controller designprocess the effective bulk modulus and leakage coefficientsare considered as variable systemparameters In order to con-sider saturation in electric motor the antiwindup algorithmpresented in Figure 8 also applies to the adaptive antiwindupPID sliding mode control scheme
8 The Scientific World Journal
Position controller BLDC motor with controller
Motorcontroller
r i re
120596
i
Ks
Ks Km
Tm
plusmn100A
minus+
+++
+
rpmplusmn10000
minus
ka
ei
s
k2s
orKi
s
k3 or Kd
k1 or Kpe 120596p1
Jms + Bm
Figure 9 Block diagram for adopted antiwindup algorithm in controller design
06 07 08 09 1 1118
19
20
21
22Upper boundary
Lower boundary
Nominal response
0 02 04 06 08 1 12 14 16 18 20
5
10
15
20
25
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
Figure 10 Step response of the optimal antiwindup PID controlsystem in computer simulation based on identified transfer functionof EHA system
The PID sliding surface 120577 for the design of the adaptivesliding mode control system is defined as [29ndash32]
120577 = 1198961
119890 + 1198962
int 119890 119889119905 + 1198963
119890 (18)
where the tracking error of the position 119890 = 119909119889
minus 119909 119909 isthe displacement of hydraulic cylinder and 119896
1
1198962
and 1198963
arepositive design parameters
The sliding mode control law consists of equivalent androbust control term that is
120596119901
= 120596119901119890119902
+ 120596119901robust (19)
By combining (11) and (18) with consideration of the noiseterm in the jerk =
119898
+ 119899
the derivative of the slidingsurface 120577 can be written as
120577 = minus 1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
120596119901
+ 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119898
+ 119899
)
+ 1198963
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+ 1198963
119889
+ 1198961
119890 + 1198962
119890
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891
(20)
where 119891 = 1198911
+ (119862119879
119860)1198912
+ (1198810
119860119863119901
120573119890
) 1198912
is lumped uncer-tain nonlinearities of the EHA system and the subscripts 119898and 119899 denote the nominal and noisy values respectively
To determine the equivalent control term 120596119901119890119902
the noiseterm in the jerk is neglected and it is assumed that the slidingsurface 120577 is at steady-state that is 120577 = 0 and then theequivalent control law can be determined as
120596119901119890119902
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119889
(21)
Thus 120577 can be rewritten as
120577 = 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119899
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891 (22)
In the standard sliding mode control to satisfy the reach-ability condition that directs system trajectories toward asliding surface where they remain and to attenuate chatteringin the control input the derivative of the sliding surface isselected as [33 34]
120577 = minus119863120577 minus 119870 sgn (120577) (23)
where119863 and119870 are positive design parameters
The Scientific World Journal 9
To determine a robust control term120596119901robust that achieves
robustness to uncertainties such as noise terms in the jerk andunmodeled system dynamics as well as the disturbance forceit is assumed that
1198630
10038161003816100381610038161205771003816100381610038161003816 + 1198700 gt
100381610038161003816100381610038161003816100381610038161003816
1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119899
+1
1198721198810
119891)
100381610038161003816100381610038161003816100381610038161003816
+ 120578
(24)
where 1198700
= (119860119863119901
120573119890
(1198611198810
+ 119862119879
119863119901
119872120573119890
))119870 and 1198630
=
(119860119863119901
120573119890
(1198611198810
+119862119879
119863119901
119872120573119890
))119863 are positive design parametersand 120578 is sufficiently small positive parameter On the assump-tion of (24) the robust control law is determined as
120596119901robust = 119863120577 + 119870 sgn (120577) (25)
Finally the sliding mode control law is selected as
120596119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 119889
+1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119863120577 + 119870 sgn (120577)
(26)
If the total leakage coefficient 119862119879
and the effective bulkmodulus of EHA systems 120573
119890
are considered as variableparameters that is 119862
119879
= 119862119879119899
+ 119862119879119901
and 120573119890
= 120573119890119899
+ 120573119890119901
then the uncertainty 120595 is defined as
120595 = 120579119879
120593 = (1198721198810
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
) 119898
+ (
(1198602
+ 119861119862119879119901
119863119901
) 120573119890119901
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)
(27)
where 120579119879
= [(1198721198810
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)) ((1198602
+
119861119862119879119901
119863119901
)120573119890119901
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
))] and 120593 = [119909
119898
119909
] Theparameter vector 120579 is considered as an unknown parametervector and it can be estimated by using the update lawFrom (26) and estimated unknown parameter vector 120579 theestimated sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119860119863119901
120573119890119899
times 119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
+ 119863120577 + 119870 sgn (120577)
(28)
In order to obtain the update law for the unknownparameters the Lyapunov candidate is defined as
119881 =1
21205772
+1
2120574120579119879
120579 (29)
where 120579 = 120579 minus 120579 120574 is a positive parameter Also 120579 and 120579 arethe nominal and estimated parameter vectors respectivelyThe derivative of the Lyapunov candidate including slidingdynamics is expressed as
= 120577 [119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
minus1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
119901
] minus1
120574120579119879120579
(30)
Substituting the estimated angular velocity of the pump 119901
given by (28) into (30) yields
= minus1198631205772
minus 119870120577 sgn (120577) + 120579119879 (120577120593 minus 1120574
120579) (31)
From the derivative of the Lyapunov included sliding dynam-ics the update law for the unknown parameters is selected as
120579 = 120574120577120593 (32)
Therefore the derivative of the Lyapunov is given as
= minus1198631205772
minus 119870120577 sgn (120577) le 0 (33)
By applying invariant set theorem for (33) the asymptoticalstability of the EHAposition control system is guaranteed [3334]
Finally the sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times (120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890)
+ 119863120577 + 119870 sgn (120577) (34)
where 120573119890
(119905 + 119879119904
) = (119889120573119890
(119905)119889119905)119879119904
+ 120573119890
(119905) 119862119879
(119905 + 119879119904
) =
(119889119862119879
(119905)119889119905)119879119904
+ 119862119879
(119905) and 119879119904
is the sampling time
10 The Scientific World Journal
Table 3 Optimal gains of optimal PID antiwindup PID and adaptive anti-windup PID sliding mode control systems in experiments
Gain Optimal PID Optimal antiwindup PID Adaptive antiwindup PID sliding modeProportional (119870
119901
or 1198961
) 10343 16947 950Integral (119870
119894
or 1198962
) 184 10877 0001Derivative (119870
119889
or 1198963
) 47 4160 145Antiwindup (119870
119886
) mdash 0001 0001
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 11 Performances of optimal PID position control system for EHA without load disturbance (only mass load is applied)
5 Experimental Results and Discussion
This section looks to the experimental results in order tocompare the performance of a position control systemsThreekinds of controllers are compared in order to show improvedperformance of overshoot reduction and robustness to theparameter change and load disturbance of the proposedcontroller for EHA position control system
Firstly optimal PID controller is designed and imple-mented by experiments Figure 11 shows experimental resultsof the PID position controller with step references of fourdifferent amplitudes which are 10 20 30 and 40mmwithoutload disturbance that is only mass load is applied as load tothe position control system
The gains of the three-position controllers are optimallyselected by using MATLABSimulink optimization toolboxbased on identified system dynamic model of (14) In theprocess of optimal gain selection the amplitude of positionreference is set to 20mm and target performance is 04seconds of the rising time 08 seconds of settling timeunder 5 of percent overshoot and under 01mm of steady-state error In experiments the optimal gains derived fromMATLABSimulink optimization toolbox are tuned to obtainbest responses The finally tuned optimal gains of the threecontrollers are represented in Table 3
As shown in Figure 11 large overshoot is observed inposition control result for using the optimal PID positioncontroller The performance of optimal PID position control
system is represented in Table 4The performance of optimalPID controller in experiment is not satisfactory the aimedvalue In detail large overshoot is observed in experimentsThe current and angular velocity saturations of BLDC motorin position experiment result of optimal PID controller areshown in Figure 12The large overshoot in position controllercan be caused due to saturation of BLDC motor as shown inFigure 12
To reduce such a large overshoot an antiwindup algo-rithmwhich is described in Figure 9 is applied to the positioncontrol system of the EHA The performance characteristicsof an antiwindup PID position controller are depicted inFigure 13 and also the values of performance indices areshown in Table 4 As shown in Figure 13 the overshoot ofthe optimal antiwindup PID controller is more diminishedthan that of the optimal PID controller However as shown inTable 4 the antiwindupPID controller still has a performanceof relatively long settling times which do not meet the aimedperformance Moreover as the amplitude of the referenceinput increases the steady-state error is increasing as shownin Figure 13
Figure 14 shows the experimental results of optimal adap-tive antiwindup sliding mode position control system for theEHA system As shown in Figure 14 the optimal antiwindupPID sliding mode position control system has a better per-formance than the system with optimal PID and antiwindupPID controllers such that relatively small overshoot and shortsettling time are obtained by the adaptive antiwindup PID
The Scientific World Journal 11
Table 4 Comparison of the performance of optimal PID optimal antiwindup PID and adaptive antiwindup PID sliding mode controlsystems without load disturbance
Performance Reference Optimal PID Optimal antiwindup PID Adaptive antiwindup PIDsliding mode
Overshoot
10mm 389 208 1020mm 161 133 0530mm 147 119 0240mm 122 82 01
Settling time
10mm 178 sec 22 sec 06 sec20mm 056 sec 22 sec 06 sec30mm 058 sec 063 sec 07 sec40mm 069 sec 26 sec 07 sec
0 05 1 15 2 25 3minus120
minus90
minus60
minus30
0
30
60
90
120
150
Impr
esse
d cu
rren
t (A
)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(a) Saturation of impressed current
0 05 1 15 2 25 3minus6000
minus4000
minus2000
0
2000
4000
6000
8000
10000
12000
14000
Mot
or an
gula
r spe
ed (r
pm)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Saturation of angular velocity
Figure 12 Saturation of BLDCmotor for optimal PID position control system for EHAwithout load disturbance (only mass load is applied)
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 13 Performances of optimal antiwindup PID position control system for EHA without load disturbance (only mass load is applied)
12 The Scientific World Journal
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 14 Performances of optimal adaptive antiwindup PID sliding mode position control system for EHA without load disturbance (onlymass load is applied)
0 05 1 15 2 25 30
1
2
3
4
5
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 15 Pressure variations of optimal PID position control system for EHA without load disturbance (only mass load is applied)
sliding mode control system As shown in Figure 14 andTable 4 the consistent performance is realized by the optimaladaptive antiwindup PID sliding mode control system Thetime-domain quantitative performance indicators are alsosummarized in Table 4 for optimal adaptive antiwindup PIDsliding mode control system without load
On the other hand Figure 15 depicts pressure variationsof the optimal PID EHAposition control systemwithout loaddisturbance As shown in Figure 15 the range of operatingpressure of the EHA system is under 3MPa inwhich the effec-tive bulk modulus can be significantly changed according tocontained air ratio of working fluid [5 7 11ndash13] as shownin Figure 16 The range of operating pressure for antiwindup
PID and antiwindup PID sliding mode control system is alsounder 3MPa
Figure 17 depicts pressures of the EHA system when theposition control systems are operating with load disturbanceAs shown in Figure 17 the maximum operating pressures ofthe EHA system is about 10MPa when the position controlsystems are working under the condition of adding distur-bance loadThemaximumoperating pressure for antiwindupPID and antiwindup PID sliding mode control system isalso up to 10MPa Thus the effective bulk modulus can bechanged greatly according to variation of operating pressureof the EHA systems In addition total leakage coefficient alsocan be changed in response to the level of working pressure
The Scientific World Journal 13
0 5 10 15 20 25 300
400
800
1200
1600
2000
Bulk
mod
ulus
(MPa
)
Pressure (MPa)
Contained air ratio ()001
110
Figure 16 Example of the relationship between pressure and effective bulk modulus [12 13]
0 05 1 15 2 25 30123456789
101112
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 17 Pressure variations of optimal PID position control system for EHA with load disturbance
In order to investigate robustness to the lumped systemuncertainties such as varying parameters and modeling errorand load disturbance the performances of the three-positioncontrollers of EHA system are compared in experiments byapplying load disturbance The experiments are conductedwith 20mm position reference and the load disturbance isapplied by controlling the opening area of servo valve whichis installed in a meter outline of load cylinder
As shown in Figure 18 the optimal PID and optimalantiwindup PID control systems do not achieve robustnessto the parameter change and load disturbance In spite of theload disturbance and saturation of the BLDC motor in theposition control system for EHA the adaptive antiwindupPID sliding mode control system has a better performanceand robustness than the optimal PID and optimal antiwindupPID control systems such that the adaptive antiwindup PID
sliding mode control system recovers the parameter changeand external disturbance in about 09 sec with a small over-shootThe time-domain quantitative performance indicatorsare summarized in Table 5 for optimal PID antiwindup PIDand adaptive antiwindup PID sliding mode control systemswith load disturbance The list of terms are represented inTable 6
6 Conclusion
This paper discussed the application of the optimal PIDcontroller with optimal control gains using the optimizationtoolbox ofMATLABSimulink to the position control systemof EHA in order to understand the basic performancecharacteristics of the system In experiment with optimal PIDcontroller large overshoot due to saturation of electric motoris observed
14 The Scientific World Journal
0 05 1 15 2 25 30
5
10
15
20
25
30
35
Position referenceOptimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(b) Position errors
0 05 1 15 2 25 30
2
4
6
8
10
Load
forc
e (kN
)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(c) Load force
Figure 18 Performances of optimal PID antiwindup PID and adaptive antiwindup PID sliding mode control systems for EHA with loaddisturbance
Table 5 Comparison of the performance of optimal PID optimalantiwindup PID and adaptive antiwindup PID slidingmode controlsystems with load disturbance
Performance OptimalPID
Optimalantiwindup PID
Adaptive antiwindupPID sliding mode
Overshoot 45 39 12Settling time 38 sec 18 sec 08 sec
In order to achieve the desirable performance of EHAposition control system optimal antiwindup PID controller
and adaptive antiwindup PID sliding mode controller arealso applied to control the position of EHA systems Inthe process of robust control system design mathematicalmodeling was carried out based on theoretical analysisand the simple third-order nominal model was derivedThe system parameters of the simple second-order nominalmodel were identified by the signal compression method
Based on the experimental results and the time-domainquantitative performance indicators the performance of theEHA position control system can be improved and robustto the load disturbance parameter variation and system
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
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DistributedSensor Networks
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The Scientific World Journal 3
Table 1 Specification of components for the EHA prototype
Specification ValuePump
Type Fixed displacement axial pistonpump (bidirectional)
Number of pistons 7Displacement 5 times 10
minus6m3
Maximum pressure 206 times 106 Pa
Motor
Type Brushless DC motorDC link voltage 270VRated current 524 ArmsRated torque 134NsdotmMax speed 10000 rpmPower 9 kW
Hydraulic cylinder
Type Double rod double actingPiston diameter 0108mDiameter of rod 0044mLength of stroke 00650mMaximum pressure 206 times 10
6 PaAccumulator
Acc Type BladderGas precharge pressure 049 times 10
6 PaAccumulator volume 07 L
Load massWeight 50 kg
DS1104 dSPACE board is used as a main control device toimplement proposed position controllers optimal PID opti-mal antiwindup PID controller and an adaptive antiwindupPID sliding mode controller The real-time control system isprogrammed by MATLABSimulink and gets transferred tothe dSPACE board through the Real-Time Workshop Theparameters of the controller implemented on the board can bechanged and monitored through the Control-Desk softwarein real time
3 Modeling of Position ControlSystem of EHA
In this section we derive a mathematical model of EHAsystems identifying system parameters by the signal com-pression method (SCM) in order to design the positioncontroller of EHA
31 Mathematical Model of EHA System Figure 3 shows theschematic diagram of EHA system As shown in Figure 3the pump inoutflows 119876
119886
119876119887
can be represented with the
Table 2 Specifications of the EHA prototype
Specifications ValuesStall force Max 1541NStroke Max plusmn337mmVelocity 1230sim1425mmsPower Max 90 kW
Servo valve and fiter
EHALoad cell
Load cylinder
Motor amplifier
Load mass
LVDT
Figure 1 Photo of the position control test rig of the EHA
pump inletoutlet chamber pressures 119901119886
119901119887
and the cylinderdisplacement 119909 as follows
119876119886
= 119863119901
120596119901
minus 120585 (119901119886
minus 119901119887
) minus119881119886
120573119890
119889119901119886
119889119905minus 119862119890119901
(119901119886
minus 119901119903
)
119876119887
= 119863119901
120596119901
minus 120585 (119901119886
minus 119901119887
) +119881119887
120573119890
119889119901119887
119889119905+ 119862119890119901
(119901119887
minus 119901119903
)
(1)
where 119863119901
is displacement of the pump 120585 is the pump crossport leakage coefficient 119862
119890119901
is the pump leakage coefficient119901119903
is the accumulator pressure 120573119890
stands for the effectivebulk modulus of the working fluid and119881
119886
119881119887
are inletoutletvolumes of pipe and cylinder chamber respectively
In addition the cylinder inletoutlet flows 1198761
1198762
can berepresented by
1198761
= 119860 +119881119886
120573119890
1198891199011
119889119905+ 119871 (119901
1
minus 1199012
)
1198762
= 119860 minus119881119887
120573119890
1198891199012
119889119905minus 119871 (119901
2
minus 1199011
)
(2)
where 119860 is pressurized area of hydraulic piston 119871 is internalleakage coefficient of the cylinder and 119901
1
1199012
are the cylinderinletoutlet chamber pressures respectively In this study theexternal leakage of the cylinder is neglected
In this study 119881119886
and 119881119887
are assumed to be equal dueto the double rod and double acting hydraulic cylinder isused in EHA system Also 119881
119886
and 119881119887
can be expressed with
4 The Scientific World Journal
Force
Reservoir
Position
M
Computer system
MATLAB Real-TimeWorkshop Simulink
Optimal PID controller
DS1104 dSPACE
Load cylinder
Main cylinder
Servo valve
Mass
Servo motordirver
Loadcontroller
LoadLVDT
AMP
cell
Figure 2 Schematic diagram for the test rig of the EHA prototype
Bidirectional variable displacement
axial piston pump
MassCylinder rod
Electricmotor
Piston
Cylinder
p1
Q1
p2
Q2
pa
Qa
pb
Qb
120596p
J
x
Figure 3 Schematic diagram of an EHA system
the nominal volume of each EHA chamber 1198810
which equalsthe mean volume of pipe and cylinder chamber as follows
119881119886
= 1198810
+ 119860119909
119881119887
= 1198810
minus 119860119909
(3)
Since a solid tubing is used in the prototype the pressureimpact of pipe expansion and flexibility on the effectivebulk modulus is assumed to be negligible Therefore therelationship pump port flows (119876
119886
119876119887
) and cylinder chamberflows (119876
1
1198762
) can be expressed as
1198761
= 119876119886
1198762
= 119876119887
(4)
Then the load 119876119871
can be defined as follows [21]
119876119871
=1198761
+ 1198762
2=119876119886
+ 119876119887
2 (5)
The relationship between the pump port pressures (119901119886
119901119887
) and cylinder chamber pressures (1199011
1199012
) can then beexpressed as
119901119886
= 1199011
+ 119901pipe
119901119887
= 1199012
minus 119901pipe(6)
where 119901pipe is pressure dropDue to the short length of tubing pump port pressures
are assumed to be equal that is the pressure drop can beneglected to the actuator inlet and outlet pressures such that[7 8 11 17 22]
119901119886
= 1199011
119901119887
= 1199012
(7)
Since the symmetrical double-rod hydraulic cylinder isused in this EHA system the following equation for thecylinder chamber pressures can be established
1198891199011
119889119905= minus
1198891199012
119889119905 (8)
By combining (1) (2) (5) (7) and (8) a simplifiedpumpcylinder model equation can be expressed as
119863119901
120596119901
= 119860 +1198810
120573119890
119871
+ 119862119879
119901119871
+ 1198911
(9)
where 119901119871
= 1199011
minus 1199012
119862119879
= 120585 + 119871 + (119862119901
2) is theequivalent leakage coefficient and 119891
1
is unmodeled dynamicsof hydraulic part of the EHA system
The actuator force and the displacement of the load canbe represented as
119865 = 119901119871
119860 = 119872 + 119861 + 1198912
(10)
The Scientific World Journal 5
where 119860 is pressurized area of hydraulic cylinder119872 is massof load 119861 is viscous friction coefficient and 119891
2
is lumpeduncertain nonlinearities due to external disturbance theunmodeled friction forces and other hard-to-model terms ofmechanical part of the EHA system
By combining (9) and (10) and neglecting 1198911
and 1198912
the linear transfer function between the angular velocity ofthe pump and the displacement of the main cylinder can beexpressed as
119866ℎ
(119904) =119909 (119904)
120596119901
(119904)
= (
119860119863119901
120573119890
1198721198810
)(1199043
+ (119861
119872+
119862119879
119863119901
120573119890
1198810
) 1199042
+
120573119890
(119861119862119879
119863119901
+ 1198602
)
1198721198810
119904)
minus1
(11)
where 119904 is the Laplace operatorBased on (11) the variation of the effective bulk modulus
of the working fluid can increase or decrease the compress-ibility of the working fluid and then the natural frequency ofthe EHA system can be adjusted meaning that the variationof the system parameters can affect the performance of theEHA position control system
On the other hand the dynamics of the BLDC motorwith controller that is electric part of the EHA system isconsidered as [14 23]
119866119898
(119904) =
120596119901
(119904)
V119903
(119904)=
119870119898
(1198791
119904 + 1)
119879119898
1
1199042
+ 119879119898
2
119904 + 1 (12)
where 119870119898
1198791
119879119898
1
and 119879119898
2
are parameters of the BLDCmotor with controller
32 Parameter Identification In general the unknown sys-tem parameters of the linear elements in a nonlinear systemcan be identified by the signal compression method (SCM)[24] In this study SCM is applied to identify the hydraulicpart of the EHA prototype
However hydraulic servo systems engage in significantnonlinear behavior due to system uncertainties such as pipelosses leakages and parameter variations of theworking fluid[9ndash11 16 17 19] Some of those uncertainties are sometimesneglected because the SCM can only identify the linear partof the system in the identification process This study thencompensates for the neglected nonlinear behavior of the EHAsystem by using a robust controller that is adaptive PIDsliding mode control scheme
As shown in Figure 4 the test signal that has the sameamplitude up to 4Hz in the frequency domain is applied tothe position control system of EHA by constructing a close-loop proportional control system to obtain a more accurateequivalent impulse response for the precise identification ofunknown parameters Figure 5 shows the comparison of thefrequency response of the position control system between
0 1 2 3 4 5 6 7 8minus3
minus25minus2
minus15minus1
minus050
051
152
253
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Figure 4 Test signal
40
50
60
70
ExperimentModel
Mag
nitu
de (d
B)
Frequency (Hz)10minus1 100 101
Figure 5 Bode plots of the closed loop nominal model and theclosed loop actual system with a proportional controller
the closed-loop nominal model and the closed-loop actualsystem with a proportional controller whose gain is 1000
The identified transfer function of a closed-loop actualsystem with a proportional controller for EHA positioncontrol system is as follows
119870119866 (119904)
1 + 119870119866 (119904)=
118 times 107
1199043
+ 22311199042
+ 718 times 105
119904 + 118 times 107
(13)
where119870 is proportional gain of closed-loop actual systemFrom the identified nominal model for the closed-loop
position control system for EHA with the proportionalcontroller the parameters of the position control system canbe acquired by eliminating the effect of the proportionalcontroller mathematically
6 The Scientific World Journal
0 1 2 3 4 5 6 7 8minus3
minus25minus2
minus15minus1
minus050
051
152
253
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
ExperimentModel
(a) Response for the test signal
0 05 1 15 2 25 3 35 4 45
0
2
4
6
8
10
12
14
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
minus2
ExperimentModel
(b) Step response
Figure 6 Time responses of the position control system obtained by the experiment and nominal model
After eliminating the effect of the proportional controllerthe identified transfer function of the hydraulic part of theEHA prototype is as follows
119866 (119904) =118 times 10
4
1199043
+ 22311199042
+ 718 times 105
119904 (14)
The identified system parameters were verified on thetime domain Figures 6(a) and 6(b) show the responseagainst test signal and the step responses of the nominalmodel and actual system respectively The validations ofthe identified parameters are estimated quantitatively by thecross-correlation as shown in [24]
Corr =sum119873
119896=1
(119884119901
(119896) minus 119884119901
) (119884119898
(119896) minus 119884119898
)
radicsum119873
119896=1
(119884119901
(119896) minus 119884119901
)radicsum119873
119896=1
(119884119898
(119896) minus 119884119898
)2
(15)
where 119884119901
(119896) and 119884119898
(119896) are the responses of the real andnominal model in time train 119896 respectively 119884
119901
and 119884119898
arethe mean values of 119884
119901
(119896) and 119884119898
(119896) 119873 is the acquired datanumberThe value of the cross-correlation is 0904 which canbe calculated from the identification results The identifiedsystem parameters are then available to controller designThe identified transfer function in (14) is used to obtain theoptimal control gains for designed position controllers byusing MATLABSimulink
In addition the dynamics characteristic of the BLDCmotor with controller is also investigated by using SCMThetransfer function of the BLDC motor with controller can besimplified to a second-order linear system as described in(12) Figure 7 shows bode plot of the actual BLDC motorwith controllerThe bandwidth of the actual open loop BLDCmotor with controller is about 400 rads The bandwidth ofthe BLDC motor with controller is 20 times larger than thatof hydraulic part of the EHA systemTherefore in this study
110
115
120
125
Experiment
Mag
nitu
de (d
B)
Frequency (Hz)100 101 102
Figure 7 Bode plots of the open-loop actual BLDC motor withcontroller system
we consider that the dynamics of BLDCmotorwith controlleris negligible because the motor dynamic is sufficiently fasterthan hydraulic part of the EHA Then the electric part ofthe EHA system is taking account of the motor gain 119870V andcurrent saturation is reflected in the controller design and thecomputer simulations stage
4 Position Controller Design fora Prototype EHA
In this study an EHA prototype is developed for appli-cation in the industrial fields As mentioned in Section 2performance characteristics such as no overshoot and rapidresponse time in position control are the typical demandsof the EHA for industrial use Therefore appropriate control
The Scientific World Journal 7
Positioncontroller
BLDC motor with controller
Hydraulic part of EHA system
Motorcontroller
r e
120596
e xi
Ks
Km
Tm 120596p
plusmn100A
minus+ minus+
rpmplusmn10000Reference position (xd) 1
Jms + Bm
x(s)
120596p(s)=
ADp120573e
e
MV0
s3 + ((BM) + (CTDp120573eV0))s2 + (120573 (BCTDp + A2)MV0)s
Figure 8 Block diagram for the position control system of the EHA
strategy should be applied to EHA position control system inorder to achieve these outcomes
Figure 8 shows the block diagram of position controlsystem of the EHA As mentioned in the previous section inFigure 8 the dynamics of the BLDC motor with controlleris considered as just the motor gain 119870
119898
and saturation ofcurrent of the BLDC motor is considered as an actuatorconstraint
In order to compare and show the desirable performancecharacteristics for the proposed EHA control system threekinds of position controllers are designed based on identifiedsimple transfer function First an optimal PID controller isdesigned and applied to the system in order to understandthe basic characteristics of EHA position control systemThe optimal antiwindup PID controller is then designed toreduce overshoot due to saturation of current in the electricmotor Finally an adaptive antiwindup PID sliding modecontroller is designed to obtain the desirable performanceand robustness against the effect of hardware saturation loaddisturbance and parameter variation
41 Optimal PID and Optimal Antiwindup PID ControlSystems An optimal PID position control system is designedto understand basic control performance of EHA prototypeAlso an optimal antiwindup PID control system for the EHAis designed to obtain desirable performance characteristicconsidering saturation in electric motor
The cost function is considered during the design ofthe optimal PID and optimal antiwindup PID controllers asfollows [25]
119869 (119870119901
119870119894
119870119889
) =
infin
sum
119905=0
(119910step (119905) minus 119910119889
step (119905)) (16)
where 119910119889step(119905) is the desired step response of the optimalPID and optimal antiwindup PID control systems and 119910step(119905)is the step response by the identified transfer function in(14)The optimal PID and optimal antiwindup PID controllerdesigns can be stated as
min119870
119901119870
119894119870
119889
119869 (119870119901
119870119894
119870119889
) (17)
where 119870119901
119870119894
and 119870119889
are the proportional integral anddifferential control gains respectively
There are many optimization algorithms in the opti-mization toolbox of MATLABSimulink The cost functionis given by (119870
119901
119870119894
119870119889
) And the gains of the optimal PIDand optimal antiwindup PID controllers 119870
119901
119870119894
and 119870119889
can be found by using the optimization toolbox of MAT-LABSimulink To find optimal control gains the referencestep input is applied in optimization process and the responseperformance is set as follows The amplitude of reference is20mm the rising time is 04 seconds settling time is 08seconds percent overshoot is under 5 and steady-stateerror is under 01mm
In the optimization process of optimal PID and optimalantiwindup PID controllers system parameter uncertaintiesdue to the modeling error are considered Specifically plusmn10ofmodeling error is considered in terms of identified transferfunction associate with variable system parameters such aseffective bulk modulus of the working fluid and total leakagecoefficient
With respect to optimal antiwindup PID and antiwindupPID sliding mode controllers the antiwindup algorithmshown in Figure 9 is used to consider saturation in an electricmotor [2 26ndash28]
Figure 10 shows the results of a computer simulationwith optimal antiwindup PID control gains using MAT-LABSimulink optimization toolbox based on identifiedtransfer function considering model uncertainty The dottedline there shows upper bound and lower bound consideringthe plusmn10 of modeling error and straight line shows nominalsimulation result with optimal antiwindup PID control gainsAs shown in Figure 10 the simulation result with optimalgains satisfies set response performance
42 Adaptive Antiwindup SlidingModeController Consideringthe PID Sliding Surface In this study the adaptive anti-windup PID sliding mode control scheme is also designedto achieve desirable performance and robustness of EHAposition control systems Throughout the controller designprocess the effective bulk modulus and leakage coefficientsare considered as variable systemparameters In order to con-sider saturation in electric motor the antiwindup algorithmpresented in Figure 8 also applies to the adaptive antiwindupPID sliding mode control scheme
8 The Scientific World Journal
Position controller BLDC motor with controller
Motorcontroller
r i re
120596
i
Ks
Ks Km
Tm
plusmn100A
minus+
+++
+
rpmplusmn10000
minus
ka
ei
s
k2s
orKi
s
k3 or Kd
k1 or Kpe 120596p1
Jms + Bm
Figure 9 Block diagram for adopted antiwindup algorithm in controller design
06 07 08 09 1 1118
19
20
21
22Upper boundary
Lower boundary
Nominal response
0 02 04 06 08 1 12 14 16 18 20
5
10
15
20
25
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
Figure 10 Step response of the optimal antiwindup PID controlsystem in computer simulation based on identified transfer functionof EHA system
The PID sliding surface 120577 for the design of the adaptivesliding mode control system is defined as [29ndash32]
120577 = 1198961
119890 + 1198962
int 119890 119889119905 + 1198963
119890 (18)
where the tracking error of the position 119890 = 119909119889
minus 119909 119909 isthe displacement of hydraulic cylinder and 119896
1
1198962
and 1198963
arepositive design parameters
The sliding mode control law consists of equivalent androbust control term that is
120596119901
= 120596119901119890119902
+ 120596119901robust (19)
By combining (11) and (18) with consideration of the noiseterm in the jerk =
119898
+ 119899
the derivative of the slidingsurface 120577 can be written as
120577 = minus 1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
120596119901
+ 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119898
+ 119899
)
+ 1198963
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+ 1198963
119889
+ 1198961
119890 + 1198962
119890
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891
(20)
where 119891 = 1198911
+ (119862119879
119860)1198912
+ (1198810
119860119863119901
120573119890
) 1198912
is lumped uncer-tain nonlinearities of the EHA system and the subscripts 119898and 119899 denote the nominal and noisy values respectively
To determine the equivalent control term 120596119901119890119902
the noiseterm in the jerk is neglected and it is assumed that the slidingsurface 120577 is at steady-state that is 120577 = 0 and then theequivalent control law can be determined as
120596119901119890119902
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119889
(21)
Thus 120577 can be rewritten as
120577 = 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119899
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891 (22)
In the standard sliding mode control to satisfy the reach-ability condition that directs system trajectories toward asliding surface where they remain and to attenuate chatteringin the control input the derivative of the sliding surface isselected as [33 34]
120577 = minus119863120577 minus 119870 sgn (120577) (23)
where119863 and119870 are positive design parameters
The Scientific World Journal 9
To determine a robust control term120596119901robust that achieves
robustness to uncertainties such as noise terms in the jerk andunmodeled system dynamics as well as the disturbance forceit is assumed that
1198630
10038161003816100381610038161205771003816100381610038161003816 + 1198700 gt
100381610038161003816100381610038161003816100381610038161003816
1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119899
+1
1198721198810
119891)
100381610038161003816100381610038161003816100381610038161003816
+ 120578
(24)
where 1198700
= (119860119863119901
120573119890
(1198611198810
+ 119862119879
119863119901
119872120573119890
))119870 and 1198630
=
(119860119863119901
120573119890
(1198611198810
+119862119879
119863119901
119872120573119890
))119863 are positive design parametersand 120578 is sufficiently small positive parameter On the assump-tion of (24) the robust control law is determined as
120596119901robust = 119863120577 + 119870 sgn (120577) (25)
Finally the sliding mode control law is selected as
120596119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 119889
+1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119863120577 + 119870 sgn (120577)
(26)
If the total leakage coefficient 119862119879
and the effective bulkmodulus of EHA systems 120573
119890
are considered as variableparameters that is 119862
119879
= 119862119879119899
+ 119862119879119901
and 120573119890
= 120573119890119899
+ 120573119890119901
then the uncertainty 120595 is defined as
120595 = 120579119879
120593 = (1198721198810
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
) 119898
+ (
(1198602
+ 119861119862119879119901
119863119901
) 120573119890119901
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)
(27)
where 120579119879
= [(1198721198810
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)) ((1198602
+
119861119862119879119901
119863119901
)120573119890119901
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
))] and 120593 = [119909
119898
119909
] Theparameter vector 120579 is considered as an unknown parametervector and it can be estimated by using the update lawFrom (26) and estimated unknown parameter vector 120579 theestimated sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119860119863119901
120573119890119899
times 119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
+ 119863120577 + 119870 sgn (120577)
(28)
In order to obtain the update law for the unknownparameters the Lyapunov candidate is defined as
119881 =1
21205772
+1
2120574120579119879
120579 (29)
where 120579 = 120579 minus 120579 120574 is a positive parameter Also 120579 and 120579 arethe nominal and estimated parameter vectors respectivelyThe derivative of the Lyapunov candidate including slidingdynamics is expressed as
= 120577 [119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
minus1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
119901
] minus1
120574120579119879120579
(30)
Substituting the estimated angular velocity of the pump 119901
given by (28) into (30) yields
= minus1198631205772
minus 119870120577 sgn (120577) + 120579119879 (120577120593 minus 1120574
120579) (31)
From the derivative of the Lyapunov included sliding dynam-ics the update law for the unknown parameters is selected as
120579 = 120574120577120593 (32)
Therefore the derivative of the Lyapunov is given as
= minus1198631205772
minus 119870120577 sgn (120577) le 0 (33)
By applying invariant set theorem for (33) the asymptoticalstability of the EHAposition control system is guaranteed [3334]
Finally the sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times (120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890)
+ 119863120577 + 119870 sgn (120577) (34)
where 120573119890
(119905 + 119879119904
) = (119889120573119890
(119905)119889119905)119879119904
+ 120573119890
(119905) 119862119879
(119905 + 119879119904
) =
(119889119862119879
(119905)119889119905)119879119904
+ 119862119879
(119905) and 119879119904
is the sampling time
10 The Scientific World Journal
Table 3 Optimal gains of optimal PID antiwindup PID and adaptive anti-windup PID sliding mode control systems in experiments
Gain Optimal PID Optimal antiwindup PID Adaptive antiwindup PID sliding modeProportional (119870
119901
or 1198961
) 10343 16947 950Integral (119870
119894
or 1198962
) 184 10877 0001Derivative (119870
119889
or 1198963
) 47 4160 145Antiwindup (119870
119886
) mdash 0001 0001
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 11 Performances of optimal PID position control system for EHA without load disturbance (only mass load is applied)
5 Experimental Results and Discussion
This section looks to the experimental results in order tocompare the performance of a position control systemsThreekinds of controllers are compared in order to show improvedperformance of overshoot reduction and robustness to theparameter change and load disturbance of the proposedcontroller for EHA position control system
Firstly optimal PID controller is designed and imple-mented by experiments Figure 11 shows experimental resultsof the PID position controller with step references of fourdifferent amplitudes which are 10 20 30 and 40mmwithoutload disturbance that is only mass load is applied as load tothe position control system
The gains of the three-position controllers are optimallyselected by using MATLABSimulink optimization toolboxbased on identified system dynamic model of (14) In theprocess of optimal gain selection the amplitude of positionreference is set to 20mm and target performance is 04seconds of the rising time 08 seconds of settling timeunder 5 of percent overshoot and under 01mm of steady-state error In experiments the optimal gains derived fromMATLABSimulink optimization toolbox are tuned to obtainbest responses The finally tuned optimal gains of the threecontrollers are represented in Table 3
As shown in Figure 11 large overshoot is observed inposition control result for using the optimal PID positioncontroller The performance of optimal PID position control
system is represented in Table 4The performance of optimalPID controller in experiment is not satisfactory the aimedvalue In detail large overshoot is observed in experimentsThe current and angular velocity saturations of BLDC motorin position experiment result of optimal PID controller areshown in Figure 12The large overshoot in position controllercan be caused due to saturation of BLDC motor as shown inFigure 12
To reduce such a large overshoot an antiwindup algo-rithmwhich is described in Figure 9 is applied to the positioncontrol system of the EHA The performance characteristicsof an antiwindup PID position controller are depicted inFigure 13 and also the values of performance indices areshown in Table 4 As shown in Figure 13 the overshoot ofthe optimal antiwindup PID controller is more diminishedthan that of the optimal PID controller However as shown inTable 4 the antiwindupPID controller still has a performanceof relatively long settling times which do not meet the aimedperformance Moreover as the amplitude of the referenceinput increases the steady-state error is increasing as shownin Figure 13
Figure 14 shows the experimental results of optimal adap-tive antiwindup sliding mode position control system for theEHA system As shown in Figure 14 the optimal antiwindupPID sliding mode position control system has a better per-formance than the system with optimal PID and antiwindupPID controllers such that relatively small overshoot and shortsettling time are obtained by the adaptive antiwindup PID
The Scientific World Journal 11
Table 4 Comparison of the performance of optimal PID optimal antiwindup PID and adaptive antiwindup PID sliding mode controlsystems without load disturbance
Performance Reference Optimal PID Optimal antiwindup PID Adaptive antiwindup PIDsliding mode
Overshoot
10mm 389 208 1020mm 161 133 0530mm 147 119 0240mm 122 82 01
Settling time
10mm 178 sec 22 sec 06 sec20mm 056 sec 22 sec 06 sec30mm 058 sec 063 sec 07 sec40mm 069 sec 26 sec 07 sec
0 05 1 15 2 25 3minus120
minus90
minus60
minus30
0
30
60
90
120
150
Impr
esse
d cu
rren
t (A
)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(a) Saturation of impressed current
0 05 1 15 2 25 3minus6000
minus4000
minus2000
0
2000
4000
6000
8000
10000
12000
14000
Mot
or an
gula
r spe
ed (r
pm)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Saturation of angular velocity
Figure 12 Saturation of BLDCmotor for optimal PID position control system for EHAwithout load disturbance (only mass load is applied)
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 13 Performances of optimal antiwindup PID position control system for EHA without load disturbance (only mass load is applied)
12 The Scientific World Journal
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 14 Performances of optimal adaptive antiwindup PID sliding mode position control system for EHA without load disturbance (onlymass load is applied)
0 05 1 15 2 25 30
1
2
3
4
5
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 15 Pressure variations of optimal PID position control system for EHA without load disturbance (only mass load is applied)
sliding mode control system As shown in Figure 14 andTable 4 the consistent performance is realized by the optimaladaptive antiwindup PID sliding mode control system Thetime-domain quantitative performance indicators are alsosummarized in Table 4 for optimal adaptive antiwindup PIDsliding mode control system without load
On the other hand Figure 15 depicts pressure variationsof the optimal PID EHAposition control systemwithout loaddisturbance As shown in Figure 15 the range of operatingpressure of the EHA system is under 3MPa inwhich the effec-tive bulk modulus can be significantly changed according tocontained air ratio of working fluid [5 7 11ndash13] as shownin Figure 16 The range of operating pressure for antiwindup
PID and antiwindup PID sliding mode control system is alsounder 3MPa
Figure 17 depicts pressures of the EHA system when theposition control systems are operating with load disturbanceAs shown in Figure 17 the maximum operating pressures ofthe EHA system is about 10MPa when the position controlsystems are working under the condition of adding distur-bance loadThemaximumoperating pressure for antiwindupPID and antiwindup PID sliding mode control system isalso up to 10MPa Thus the effective bulk modulus can bechanged greatly according to variation of operating pressureof the EHA systems In addition total leakage coefficient alsocan be changed in response to the level of working pressure
The Scientific World Journal 13
0 5 10 15 20 25 300
400
800
1200
1600
2000
Bulk
mod
ulus
(MPa
)
Pressure (MPa)
Contained air ratio ()001
110
Figure 16 Example of the relationship between pressure and effective bulk modulus [12 13]
0 05 1 15 2 25 30123456789
101112
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 17 Pressure variations of optimal PID position control system for EHA with load disturbance
In order to investigate robustness to the lumped systemuncertainties such as varying parameters and modeling errorand load disturbance the performances of the three-positioncontrollers of EHA system are compared in experiments byapplying load disturbance The experiments are conductedwith 20mm position reference and the load disturbance isapplied by controlling the opening area of servo valve whichis installed in a meter outline of load cylinder
As shown in Figure 18 the optimal PID and optimalantiwindup PID control systems do not achieve robustnessto the parameter change and load disturbance In spite of theload disturbance and saturation of the BLDC motor in theposition control system for EHA the adaptive antiwindupPID sliding mode control system has a better performanceand robustness than the optimal PID and optimal antiwindupPID control systems such that the adaptive antiwindup PID
sliding mode control system recovers the parameter changeand external disturbance in about 09 sec with a small over-shootThe time-domain quantitative performance indicatorsare summarized in Table 5 for optimal PID antiwindup PIDand adaptive antiwindup PID sliding mode control systemswith load disturbance The list of terms are represented inTable 6
6 Conclusion
This paper discussed the application of the optimal PIDcontroller with optimal control gains using the optimizationtoolbox ofMATLABSimulink to the position control systemof EHA in order to understand the basic performancecharacteristics of the system In experiment with optimal PIDcontroller large overshoot due to saturation of electric motoris observed
14 The Scientific World Journal
0 05 1 15 2 25 30
5
10
15
20
25
30
35
Position referenceOptimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(b) Position errors
0 05 1 15 2 25 30
2
4
6
8
10
Load
forc
e (kN
)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(c) Load force
Figure 18 Performances of optimal PID antiwindup PID and adaptive antiwindup PID sliding mode control systems for EHA with loaddisturbance
Table 5 Comparison of the performance of optimal PID optimalantiwindup PID and adaptive antiwindup PID slidingmode controlsystems with load disturbance
Performance OptimalPID
Optimalantiwindup PID
Adaptive antiwindupPID sliding mode
Overshoot 45 39 12Settling time 38 sec 18 sec 08 sec
In order to achieve the desirable performance of EHAposition control system optimal antiwindup PID controller
and adaptive antiwindup PID sliding mode controller arealso applied to control the position of EHA systems Inthe process of robust control system design mathematicalmodeling was carried out based on theoretical analysisand the simple third-order nominal model was derivedThe system parameters of the simple second-order nominalmodel were identified by the signal compression method
Based on the experimental results and the time-domainquantitative performance indicators the performance of theEHA position control system can be improved and robustto the load disturbance parameter variation and system
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
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International Journal of
![Page 4: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/4.jpg)
4 The Scientific World Journal
Force
Reservoir
Position
M
Computer system
MATLAB Real-TimeWorkshop Simulink
Optimal PID controller
DS1104 dSPACE
Load cylinder
Main cylinder
Servo valve
Mass
Servo motordirver
Loadcontroller
LoadLVDT
AMP
cell
Figure 2 Schematic diagram for the test rig of the EHA prototype
Bidirectional variable displacement
axial piston pump
MassCylinder rod
Electricmotor
Piston
Cylinder
p1
Q1
p2
Q2
pa
Qa
pb
Qb
120596p
J
x
Figure 3 Schematic diagram of an EHA system
the nominal volume of each EHA chamber 1198810
which equalsthe mean volume of pipe and cylinder chamber as follows
119881119886
= 1198810
+ 119860119909
119881119887
= 1198810
minus 119860119909
(3)
Since a solid tubing is used in the prototype the pressureimpact of pipe expansion and flexibility on the effectivebulk modulus is assumed to be negligible Therefore therelationship pump port flows (119876
119886
119876119887
) and cylinder chamberflows (119876
1
1198762
) can be expressed as
1198761
= 119876119886
1198762
= 119876119887
(4)
Then the load 119876119871
can be defined as follows [21]
119876119871
=1198761
+ 1198762
2=119876119886
+ 119876119887
2 (5)
The relationship between the pump port pressures (119901119886
119901119887
) and cylinder chamber pressures (1199011
1199012
) can then beexpressed as
119901119886
= 1199011
+ 119901pipe
119901119887
= 1199012
minus 119901pipe(6)
where 119901pipe is pressure dropDue to the short length of tubing pump port pressures
are assumed to be equal that is the pressure drop can beneglected to the actuator inlet and outlet pressures such that[7 8 11 17 22]
119901119886
= 1199011
119901119887
= 1199012
(7)
Since the symmetrical double-rod hydraulic cylinder isused in this EHA system the following equation for thecylinder chamber pressures can be established
1198891199011
119889119905= minus
1198891199012
119889119905 (8)
By combining (1) (2) (5) (7) and (8) a simplifiedpumpcylinder model equation can be expressed as
119863119901
120596119901
= 119860 +1198810
120573119890
119871
+ 119862119879
119901119871
+ 1198911
(9)
where 119901119871
= 1199011
minus 1199012
119862119879
= 120585 + 119871 + (119862119901
2) is theequivalent leakage coefficient and 119891
1
is unmodeled dynamicsof hydraulic part of the EHA system
The actuator force and the displacement of the load canbe represented as
119865 = 119901119871
119860 = 119872 + 119861 + 1198912
(10)
The Scientific World Journal 5
where 119860 is pressurized area of hydraulic cylinder119872 is massof load 119861 is viscous friction coefficient and 119891
2
is lumpeduncertain nonlinearities due to external disturbance theunmodeled friction forces and other hard-to-model terms ofmechanical part of the EHA system
By combining (9) and (10) and neglecting 1198911
and 1198912
the linear transfer function between the angular velocity ofthe pump and the displacement of the main cylinder can beexpressed as
119866ℎ
(119904) =119909 (119904)
120596119901
(119904)
= (
119860119863119901
120573119890
1198721198810
)(1199043
+ (119861
119872+
119862119879
119863119901
120573119890
1198810
) 1199042
+
120573119890
(119861119862119879
119863119901
+ 1198602
)
1198721198810
119904)
minus1
(11)
where 119904 is the Laplace operatorBased on (11) the variation of the effective bulk modulus
of the working fluid can increase or decrease the compress-ibility of the working fluid and then the natural frequency ofthe EHA system can be adjusted meaning that the variationof the system parameters can affect the performance of theEHA position control system
On the other hand the dynamics of the BLDC motorwith controller that is electric part of the EHA system isconsidered as [14 23]
119866119898
(119904) =
120596119901
(119904)
V119903
(119904)=
119870119898
(1198791
119904 + 1)
119879119898
1
1199042
+ 119879119898
2
119904 + 1 (12)
where 119870119898
1198791
119879119898
1
and 119879119898
2
are parameters of the BLDCmotor with controller
32 Parameter Identification In general the unknown sys-tem parameters of the linear elements in a nonlinear systemcan be identified by the signal compression method (SCM)[24] In this study SCM is applied to identify the hydraulicpart of the EHA prototype
However hydraulic servo systems engage in significantnonlinear behavior due to system uncertainties such as pipelosses leakages and parameter variations of theworking fluid[9ndash11 16 17 19] Some of those uncertainties are sometimesneglected because the SCM can only identify the linear partof the system in the identification process This study thencompensates for the neglected nonlinear behavior of the EHAsystem by using a robust controller that is adaptive PIDsliding mode control scheme
As shown in Figure 4 the test signal that has the sameamplitude up to 4Hz in the frequency domain is applied tothe position control system of EHA by constructing a close-loop proportional control system to obtain a more accurateequivalent impulse response for the precise identification ofunknown parameters Figure 5 shows the comparison of thefrequency response of the position control system between
0 1 2 3 4 5 6 7 8minus3
minus25minus2
minus15minus1
minus050
051
152
253
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Figure 4 Test signal
40
50
60
70
ExperimentModel
Mag
nitu
de (d
B)
Frequency (Hz)10minus1 100 101
Figure 5 Bode plots of the closed loop nominal model and theclosed loop actual system with a proportional controller
the closed-loop nominal model and the closed-loop actualsystem with a proportional controller whose gain is 1000
The identified transfer function of a closed-loop actualsystem with a proportional controller for EHA positioncontrol system is as follows
119870119866 (119904)
1 + 119870119866 (119904)=
118 times 107
1199043
+ 22311199042
+ 718 times 105
119904 + 118 times 107
(13)
where119870 is proportional gain of closed-loop actual systemFrom the identified nominal model for the closed-loop
position control system for EHA with the proportionalcontroller the parameters of the position control system canbe acquired by eliminating the effect of the proportionalcontroller mathematically
6 The Scientific World Journal
0 1 2 3 4 5 6 7 8minus3
minus25minus2
minus15minus1
minus050
051
152
253
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
ExperimentModel
(a) Response for the test signal
0 05 1 15 2 25 3 35 4 45
0
2
4
6
8
10
12
14
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
minus2
ExperimentModel
(b) Step response
Figure 6 Time responses of the position control system obtained by the experiment and nominal model
After eliminating the effect of the proportional controllerthe identified transfer function of the hydraulic part of theEHA prototype is as follows
119866 (119904) =118 times 10
4
1199043
+ 22311199042
+ 718 times 105
119904 (14)
The identified system parameters were verified on thetime domain Figures 6(a) and 6(b) show the responseagainst test signal and the step responses of the nominalmodel and actual system respectively The validations ofthe identified parameters are estimated quantitatively by thecross-correlation as shown in [24]
Corr =sum119873
119896=1
(119884119901
(119896) minus 119884119901
) (119884119898
(119896) minus 119884119898
)
radicsum119873
119896=1
(119884119901
(119896) minus 119884119901
)radicsum119873
119896=1
(119884119898
(119896) minus 119884119898
)2
(15)
where 119884119901
(119896) and 119884119898
(119896) are the responses of the real andnominal model in time train 119896 respectively 119884
119901
and 119884119898
arethe mean values of 119884
119901
(119896) and 119884119898
(119896) 119873 is the acquired datanumberThe value of the cross-correlation is 0904 which canbe calculated from the identification results The identifiedsystem parameters are then available to controller designThe identified transfer function in (14) is used to obtain theoptimal control gains for designed position controllers byusing MATLABSimulink
In addition the dynamics characteristic of the BLDCmotor with controller is also investigated by using SCMThetransfer function of the BLDC motor with controller can besimplified to a second-order linear system as described in(12) Figure 7 shows bode plot of the actual BLDC motorwith controllerThe bandwidth of the actual open loop BLDCmotor with controller is about 400 rads The bandwidth ofthe BLDC motor with controller is 20 times larger than thatof hydraulic part of the EHA systemTherefore in this study
110
115
120
125
Experiment
Mag
nitu
de (d
B)
Frequency (Hz)100 101 102
Figure 7 Bode plots of the open-loop actual BLDC motor withcontroller system
we consider that the dynamics of BLDCmotorwith controlleris negligible because the motor dynamic is sufficiently fasterthan hydraulic part of the EHA Then the electric part ofthe EHA system is taking account of the motor gain 119870V andcurrent saturation is reflected in the controller design and thecomputer simulations stage
4 Position Controller Design fora Prototype EHA
In this study an EHA prototype is developed for appli-cation in the industrial fields As mentioned in Section 2performance characteristics such as no overshoot and rapidresponse time in position control are the typical demandsof the EHA for industrial use Therefore appropriate control
The Scientific World Journal 7
Positioncontroller
BLDC motor with controller
Hydraulic part of EHA system
Motorcontroller
r e
120596
e xi
Ks
Km
Tm 120596p
plusmn100A
minus+ minus+
rpmplusmn10000Reference position (xd) 1
Jms + Bm
x(s)
120596p(s)=
ADp120573e
e
MV0
s3 + ((BM) + (CTDp120573eV0))s2 + (120573 (BCTDp + A2)MV0)s
Figure 8 Block diagram for the position control system of the EHA
strategy should be applied to EHA position control system inorder to achieve these outcomes
Figure 8 shows the block diagram of position controlsystem of the EHA As mentioned in the previous section inFigure 8 the dynamics of the BLDC motor with controlleris considered as just the motor gain 119870
119898
and saturation ofcurrent of the BLDC motor is considered as an actuatorconstraint
In order to compare and show the desirable performancecharacteristics for the proposed EHA control system threekinds of position controllers are designed based on identifiedsimple transfer function First an optimal PID controller isdesigned and applied to the system in order to understandthe basic characteristics of EHA position control systemThe optimal antiwindup PID controller is then designed toreduce overshoot due to saturation of current in the electricmotor Finally an adaptive antiwindup PID sliding modecontroller is designed to obtain the desirable performanceand robustness against the effect of hardware saturation loaddisturbance and parameter variation
41 Optimal PID and Optimal Antiwindup PID ControlSystems An optimal PID position control system is designedto understand basic control performance of EHA prototypeAlso an optimal antiwindup PID control system for the EHAis designed to obtain desirable performance characteristicconsidering saturation in electric motor
The cost function is considered during the design ofthe optimal PID and optimal antiwindup PID controllers asfollows [25]
119869 (119870119901
119870119894
119870119889
) =
infin
sum
119905=0
(119910step (119905) minus 119910119889
step (119905)) (16)
where 119910119889step(119905) is the desired step response of the optimalPID and optimal antiwindup PID control systems and 119910step(119905)is the step response by the identified transfer function in(14)The optimal PID and optimal antiwindup PID controllerdesigns can be stated as
min119870
119901119870
119894119870
119889
119869 (119870119901
119870119894
119870119889
) (17)
where 119870119901
119870119894
and 119870119889
are the proportional integral anddifferential control gains respectively
There are many optimization algorithms in the opti-mization toolbox of MATLABSimulink The cost functionis given by (119870
119901
119870119894
119870119889
) And the gains of the optimal PIDand optimal antiwindup PID controllers 119870
119901
119870119894
and 119870119889
can be found by using the optimization toolbox of MAT-LABSimulink To find optimal control gains the referencestep input is applied in optimization process and the responseperformance is set as follows The amplitude of reference is20mm the rising time is 04 seconds settling time is 08seconds percent overshoot is under 5 and steady-stateerror is under 01mm
In the optimization process of optimal PID and optimalantiwindup PID controllers system parameter uncertaintiesdue to the modeling error are considered Specifically plusmn10ofmodeling error is considered in terms of identified transferfunction associate with variable system parameters such aseffective bulk modulus of the working fluid and total leakagecoefficient
With respect to optimal antiwindup PID and antiwindupPID sliding mode controllers the antiwindup algorithmshown in Figure 9 is used to consider saturation in an electricmotor [2 26ndash28]
Figure 10 shows the results of a computer simulationwith optimal antiwindup PID control gains using MAT-LABSimulink optimization toolbox based on identifiedtransfer function considering model uncertainty The dottedline there shows upper bound and lower bound consideringthe plusmn10 of modeling error and straight line shows nominalsimulation result with optimal antiwindup PID control gainsAs shown in Figure 10 the simulation result with optimalgains satisfies set response performance
42 Adaptive Antiwindup SlidingModeController Consideringthe PID Sliding Surface In this study the adaptive anti-windup PID sliding mode control scheme is also designedto achieve desirable performance and robustness of EHAposition control systems Throughout the controller designprocess the effective bulk modulus and leakage coefficientsare considered as variable systemparameters In order to con-sider saturation in electric motor the antiwindup algorithmpresented in Figure 8 also applies to the adaptive antiwindupPID sliding mode control scheme
8 The Scientific World Journal
Position controller BLDC motor with controller
Motorcontroller
r i re
120596
i
Ks
Ks Km
Tm
plusmn100A
minus+
+++
+
rpmplusmn10000
minus
ka
ei
s
k2s
orKi
s
k3 or Kd
k1 or Kpe 120596p1
Jms + Bm
Figure 9 Block diagram for adopted antiwindup algorithm in controller design
06 07 08 09 1 1118
19
20
21
22Upper boundary
Lower boundary
Nominal response
0 02 04 06 08 1 12 14 16 18 20
5
10
15
20
25
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
Figure 10 Step response of the optimal antiwindup PID controlsystem in computer simulation based on identified transfer functionof EHA system
The PID sliding surface 120577 for the design of the adaptivesliding mode control system is defined as [29ndash32]
120577 = 1198961
119890 + 1198962
int 119890 119889119905 + 1198963
119890 (18)
where the tracking error of the position 119890 = 119909119889
minus 119909 119909 isthe displacement of hydraulic cylinder and 119896
1
1198962
and 1198963
arepositive design parameters
The sliding mode control law consists of equivalent androbust control term that is
120596119901
= 120596119901119890119902
+ 120596119901robust (19)
By combining (11) and (18) with consideration of the noiseterm in the jerk =
119898
+ 119899
the derivative of the slidingsurface 120577 can be written as
120577 = minus 1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
120596119901
+ 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119898
+ 119899
)
+ 1198963
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+ 1198963
119889
+ 1198961
119890 + 1198962
119890
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891
(20)
where 119891 = 1198911
+ (119862119879
119860)1198912
+ (1198810
119860119863119901
120573119890
) 1198912
is lumped uncer-tain nonlinearities of the EHA system and the subscripts 119898and 119899 denote the nominal and noisy values respectively
To determine the equivalent control term 120596119901119890119902
the noiseterm in the jerk is neglected and it is assumed that the slidingsurface 120577 is at steady-state that is 120577 = 0 and then theequivalent control law can be determined as
120596119901119890119902
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119889
(21)
Thus 120577 can be rewritten as
120577 = 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119899
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891 (22)
In the standard sliding mode control to satisfy the reach-ability condition that directs system trajectories toward asliding surface where they remain and to attenuate chatteringin the control input the derivative of the sliding surface isselected as [33 34]
120577 = minus119863120577 minus 119870 sgn (120577) (23)
where119863 and119870 are positive design parameters
The Scientific World Journal 9
To determine a robust control term120596119901robust that achieves
robustness to uncertainties such as noise terms in the jerk andunmodeled system dynamics as well as the disturbance forceit is assumed that
1198630
10038161003816100381610038161205771003816100381610038161003816 + 1198700 gt
100381610038161003816100381610038161003816100381610038161003816
1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119899
+1
1198721198810
119891)
100381610038161003816100381610038161003816100381610038161003816
+ 120578
(24)
where 1198700
= (119860119863119901
120573119890
(1198611198810
+ 119862119879
119863119901
119872120573119890
))119870 and 1198630
=
(119860119863119901
120573119890
(1198611198810
+119862119879
119863119901
119872120573119890
))119863 are positive design parametersand 120578 is sufficiently small positive parameter On the assump-tion of (24) the robust control law is determined as
120596119901robust = 119863120577 + 119870 sgn (120577) (25)
Finally the sliding mode control law is selected as
120596119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 119889
+1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119863120577 + 119870 sgn (120577)
(26)
If the total leakage coefficient 119862119879
and the effective bulkmodulus of EHA systems 120573
119890
are considered as variableparameters that is 119862
119879
= 119862119879119899
+ 119862119879119901
and 120573119890
= 120573119890119899
+ 120573119890119901
then the uncertainty 120595 is defined as
120595 = 120579119879
120593 = (1198721198810
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
) 119898
+ (
(1198602
+ 119861119862119879119901
119863119901
) 120573119890119901
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)
(27)
where 120579119879
= [(1198721198810
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)) ((1198602
+
119861119862119879119901
119863119901
)120573119890119901
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
))] and 120593 = [119909
119898
119909
] Theparameter vector 120579 is considered as an unknown parametervector and it can be estimated by using the update lawFrom (26) and estimated unknown parameter vector 120579 theestimated sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119860119863119901
120573119890119899
times 119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
+ 119863120577 + 119870 sgn (120577)
(28)
In order to obtain the update law for the unknownparameters the Lyapunov candidate is defined as
119881 =1
21205772
+1
2120574120579119879
120579 (29)
where 120579 = 120579 minus 120579 120574 is a positive parameter Also 120579 and 120579 arethe nominal and estimated parameter vectors respectivelyThe derivative of the Lyapunov candidate including slidingdynamics is expressed as
= 120577 [119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
minus1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
119901
] minus1
120574120579119879120579
(30)
Substituting the estimated angular velocity of the pump 119901
given by (28) into (30) yields
= minus1198631205772
minus 119870120577 sgn (120577) + 120579119879 (120577120593 minus 1120574
120579) (31)
From the derivative of the Lyapunov included sliding dynam-ics the update law for the unknown parameters is selected as
120579 = 120574120577120593 (32)
Therefore the derivative of the Lyapunov is given as
= minus1198631205772
minus 119870120577 sgn (120577) le 0 (33)
By applying invariant set theorem for (33) the asymptoticalstability of the EHAposition control system is guaranteed [3334]
Finally the sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times (120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890)
+ 119863120577 + 119870 sgn (120577) (34)
where 120573119890
(119905 + 119879119904
) = (119889120573119890
(119905)119889119905)119879119904
+ 120573119890
(119905) 119862119879
(119905 + 119879119904
) =
(119889119862119879
(119905)119889119905)119879119904
+ 119862119879
(119905) and 119879119904
is the sampling time
10 The Scientific World Journal
Table 3 Optimal gains of optimal PID antiwindup PID and adaptive anti-windup PID sliding mode control systems in experiments
Gain Optimal PID Optimal antiwindup PID Adaptive antiwindup PID sliding modeProportional (119870
119901
or 1198961
) 10343 16947 950Integral (119870
119894
or 1198962
) 184 10877 0001Derivative (119870
119889
or 1198963
) 47 4160 145Antiwindup (119870
119886
) mdash 0001 0001
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 11 Performances of optimal PID position control system for EHA without load disturbance (only mass load is applied)
5 Experimental Results and Discussion
This section looks to the experimental results in order tocompare the performance of a position control systemsThreekinds of controllers are compared in order to show improvedperformance of overshoot reduction and robustness to theparameter change and load disturbance of the proposedcontroller for EHA position control system
Firstly optimal PID controller is designed and imple-mented by experiments Figure 11 shows experimental resultsof the PID position controller with step references of fourdifferent amplitudes which are 10 20 30 and 40mmwithoutload disturbance that is only mass load is applied as load tothe position control system
The gains of the three-position controllers are optimallyselected by using MATLABSimulink optimization toolboxbased on identified system dynamic model of (14) In theprocess of optimal gain selection the amplitude of positionreference is set to 20mm and target performance is 04seconds of the rising time 08 seconds of settling timeunder 5 of percent overshoot and under 01mm of steady-state error In experiments the optimal gains derived fromMATLABSimulink optimization toolbox are tuned to obtainbest responses The finally tuned optimal gains of the threecontrollers are represented in Table 3
As shown in Figure 11 large overshoot is observed inposition control result for using the optimal PID positioncontroller The performance of optimal PID position control
system is represented in Table 4The performance of optimalPID controller in experiment is not satisfactory the aimedvalue In detail large overshoot is observed in experimentsThe current and angular velocity saturations of BLDC motorin position experiment result of optimal PID controller areshown in Figure 12The large overshoot in position controllercan be caused due to saturation of BLDC motor as shown inFigure 12
To reduce such a large overshoot an antiwindup algo-rithmwhich is described in Figure 9 is applied to the positioncontrol system of the EHA The performance characteristicsof an antiwindup PID position controller are depicted inFigure 13 and also the values of performance indices areshown in Table 4 As shown in Figure 13 the overshoot ofthe optimal antiwindup PID controller is more diminishedthan that of the optimal PID controller However as shown inTable 4 the antiwindupPID controller still has a performanceof relatively long settling times which do not meet the aimedperformance Moreover as the amplitude of the referenceinput increases the steady-state error is increasing as shownin Figure 13
Figure 14 shows the experimental results of optimal adap-tive antiwindup sliding mode position control system for theEHA system As shown in Figure 14 the optimal antiwindupPID sliding mode position control system has a better per-formance than the system with optimal PID and antiwindupPID controllers such that relatively small overshoot and shortsettling time are obtained by the adaptive antiwindup PID
The Scientific World Journal 11
Table 4 Comparison of the performance of optimal PID optimal antiwindup PID and adaptive antiwindup PID sliding mode controlsystems without load disturbance
Performance Reference Optimal PID Optimal antiwindup PID Adaptive antiwindup PIDsliding mode
Overshoot
10mm 389 208 1020mm 161 133 0530mm 147 119 0240mm 122 82 01
Settling time
10mm 178 sec 22 sec 06 sec20mm 056 sec 22 sec 06 sec30mm 058 sec 063 sec 07 sec40mm 069 sec 26 sec 07 sec
0 05 1 15 2 25 3minus120
minus90
minus60
minus30
0
30
60
90
120
150
Impr
esse
d cu
rren
t (A
)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(a) Saturation of impressed current
0 05 1 15 2 25 3minus6000
minus4000
minus2000
0
2000
4000
6000
8000
10000
12000
14000
Mot
or an
gula
r spe
ed (r
pm)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Saturation of angular velocity
Figure 12 Saturation of BLDCmotor for optimal PID position control system for EHAwithout load disturbance (only mass load is applied)
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 13 Performances of optimal antiwindup PID position control system for EHA without load disturbance (only mass load is applied)
12 The Scientific World Journal
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 14 Performances of optimal adaptive antiwindup PID sliding mode position control system for EHA without load disturbance (onlymass load is applied)
0 05 1 15 2 25 30
1
2
3
4
5
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 15 Pressure variations of optimal PID position control system for EHA without load disturbance (only mass load is applied)
sliding mode control system As shown in Figure 14 andTable 4 the consistent performance is realized by the optimaladaptive antiwindup PID sliding mode control system Thetime-domain quantitative performance indicators are alsosummarized in Table 4 for optimal adaptive antiwindup PIDsliding mode control system without load
On the other hand Figure 15 depicts pressure variationsof the optimal PID EHAposition control systemwithout loaddisturbance As shown in Figure 15 the range of operatingpressure of the EHA system is under 3MPa inwhich the effec-tive bulk modulus can be significantly changed according tocontained air ratio of working fluid [5 7 11ndash13] as shownin Figure 16 The range of operating pressure for antiwindup
PID and antiwindup PID sliding mode control system is alsounder 3MPa
Figure 17 depicts pressures of the EHA system when theposition control systems are operating with load disturbanceAs shown in Figure 17 the maximum operating pressures ofthe EHA system is about 10MPa when the position controlsystems are working under the condition of adding distur-bance loadThemaximumoperating pressure for antiwindupPID and antiwindup PID sliding mode control system isalso up to 10MPa Thus the effective bulk modulus can bechanged greatly according to variation of operating pressureof the EHA systems In addition total leakage coefficient alsocan be changed in response to the level of working pressure
The Scientific World Journal 13
0 5 10 15 20 25 300
400
800
1200
1600
2000
Bulk
mod
ulus
(MPa
)
Pressure (MPa)
Contained air ratio ()001
110
Figure 16 Example of the relationship between pressure and effective bulk modulus [12 13]
0 05 1 15 2 25 30123456789
101112
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 17 Pressure variations of optimal PID position control system for EHA with load disturbance
In order to investigate robustness to the lumped systemuncertainties such as varying parameters and modeling errorand load disturbance the performances of the three-positioncontrollers of EHA system are compared in experiments byapplying load disturbance The experiments are conductedwith 20mm position reference and the load disturbance isapplied by controlling the opening area of servo valve whichis installed in a meter outline of load cylinder
As shown in Figure 18 the optimal PID and optimalantiwindup PID control systems do not achieve robustnessto the parameter change and load disturbance In spite of theload disturbance and saturation of the BLDC motor in theposition control system for EHA the adaptive antiwindupPID sliding mode control system has a better performanceand robustness than the optimal PID and optimal antiwindupPID control systems such that the adaptive antiwindup PID
sliding mode control system recovers the parameter changeand external disturbance in about 09 sec with a small over-shootThe time-domain quantitative performance indicatorsare summarized in Table 5 for optimal PID antiwindup PIDand adaptive antiwindup PID sliding mode control systemswith load disturbance The list of terms are represented inTable 6
6 Conclusion
This paper discussed the application of the optimal PIDcontroller with optimal control gains using the optimizationtoolbox ofMATLABSimulink to the position control systemof EHA in order to understand the basic performancecharacteristics of the system In experiment with optimal PIDcontroller large overshoot due to saturation of electric motoris observed
14 The Scientific World Journal
0 05 1 15 2 25 30
5
10
15
20
25
30
35
Position referenceOptimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(b) Position errors
0 05 1 15 2 25 30
2
4
6
8
10
Load
forc
e (kN
)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(c) Load force
Figure 18 Performances of optimal PID antiwindup PID and adaptive antiwindup PID sliding mode control systems for EHA with loaddisturbance
Table 5 Comparison of the performance of optimal PID optimalantiwindup PID and adaptive antiwindup PID slidingmode controlsystems with load disturbance
Performance OptimalPID
Optimalantiwindup PID
Adaptive antiwindupPID sliding mode
Overshoot 45 39 12Settling time 38 sec 18 sec 08 sec
In order to achieve the desirable performance of EHAposition control system optimal antiwindup PID controller
and adaptive antiwindup PID sliding mode controller arealso applied to control the position of EHA systems Inthe process of robust control system design mathematicalmodeling was carried out based on theoretical analysisand the simple third-order nominal model was derivedThe system parameters of the simple second-order nominalmodel were identified by the signal compression method
Based on the experimental results and the time-domainquantitative performance indicators the performance of theEHA position control system can be improved and robustto the load disturbance parameter variation and system
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
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International Journal of
![Page 5: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/5.jpg)
The Scientific World Journal 5
where 119860 is pressurized area of hydraulic cylinder119872 is massof load 119861 is viscous friction coefficient and 119891
2
is lumpeduncertain nonlinearities due to external disturbance theunmodeled friction forces and other hard-to-model terms ofmechanical part of the EHA system
By combining (9) and (10) and neglecting 1198911
and 1198912
the linear transfer function between the angular velocity ofthe pump and the displacement of the main cylinder can beexpressed as
119866ℎ
(119904) =119909 (119904)
120596119901
(119904)
= (
119860119863119901
120573119890
1198721198810
)(1199043
+ (119861
119872+
119862119879
119863119901
120573119890
1198810
) 1199042
+
120573119890
(119861119862119879
119863119901
+ 1198602
)
1198721198810
119904)
minus1
(11)
where 119904 is the Laplace operatorBased on (11) the variation of the effective bulk modulus
of the working fluid can increase or decrease the compress-ibility of the working fluid and then the natural frequency ofthe EHA system can be adjusted meaning that the variationof the system parameters can affect the performance of theEHA position control system
On the other hand the dynamics of the BLDC motorwith controller that is electric part of the EHA system isconsidered as [14 23]
119866119898
(119904) =
120596119901
(119904)
V119903
(119904)=
119870119898
(1198791
119904 + 1)
119879119898
1
1199042
+ 119879119898
2
119904 + 1 (12)
where 119870119898
1198791
119879119898
1
and 119879119898
2
are parameters of the BLDCmotor with controller
32 Parameter Identification In general the unknown sys-tem parameters of the linear elements in a nonlinear systemcan be identified by the signal compression method (SCM)[24] In this study SCM is applied to identify the hydraulicpart of the EHA prototype
However hydraulic servo systems engage in significantnonlinear behavior due to system uncertainties such as pipelosses leakages and parameter variations of theworking fluid[9ndash11 16 17 19] Some of those uncertainties are sometimesneglected because the SCM can only identify the linear partof the system in the identification process This study thencompensates for the neglected nonlinear behavior of the EHAsystem by using a robust controller that is adaptive PIDsliding mode control scheme
As shown in Figure 4 the test signal that has the sameamplitude up to 4Hz in the frequency domain is applied tothe position control system of EHA by constructing a close-loop proportional control system to obtain a more accurateequivalent impulse response for the precise identification ofunknown parameters Figure 5 shows the comparison of thefrequency response of the position control system between
0 1 2 3 4 5 6 7 8minus3
minus25minus2
minus15minus1
minus050
051
152
253
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Figure 4 Test signal
40
50
60
70
ExperimentModel
Mag
nitu
de (d
B)
Frequency (Hz)10minus1 100 101
Figure 5 Bode plots of the closed loop nominal model and theclosed loop actual system with a proportional controller
the closed-loop nominal model and the closed-loop actualsystem with a proportional controller whose gain is 1000
The identified transfer function of a closed-loop actualsystem with a proportional controller for EHA positioncontrol system is as follows
119870119866 (119904)
1 + 119870119866 (119904)=
118 times 107
1199043
+ 22311199042
+ 718 times 105
119904 + 118 times 107
(13)
where119870 is proportional gain of closed-loop actual systemFrom the identified nominal model for the closed-loop
position control system for EHA with the proportionalcontroller the parameters of the position control system canbe acquired by eliminating the effect of the proportionalcontroller mathematically
6 The Scientific World Journal
0 1 2 3 4 5 6 7 8minus3
minus25minus2
minus15minus1
minus050
051
152
253
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
ExperimentModel
(a) Response for the test signal
0 05 1 15 2 25 3 35 4 45
0
2
4
6
8
10
12
14
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
minus2
ExperimentModel
(b) Step response
Figure 6 Time responses of the position control system obtained by the experiment and nominal model
After eliminating the effect of the proportional controllerthe identified transfer function of the hydraulic part of theEHA prototype is as follows
119866 (119904) =118 times 10
4
1199043
+ 22311199042
+ 718 times 105
119904 (14)
The identified system parameters were verified on thetime domain Figures 6(a) and 6(b) show the responseagainst test signal and the step responses of the nominalmodel and actual system respectively The validations ofthe identified parameters are estimated quantitatively by thecross-correlation as shown in [24]
Corr =sum119873
119896=1
(119884119901
(119896) minus 119884119901
) (119884119898
(119896) minus 119884119898
)
radicsum119873
119896=1
(119884119901
(119896) minus 119884119901
)radicsum119873
119896=1
(119884119898
(119896) minus 119884119898
)2
(15)
where 119884119901
(119896) and 119884119898
(119896) are the responses of the real andnominal model in time train 119896 respectively 119884
119901
and 119884119898
arethe mean values of 119884
119901
(119896) and 119884119898
(119896) 119873 is the acquired datanumberThe value of the cross-correlation is 0904 which canbe calculated from the identification results The identifiedsystem parameters are then available to controller designThe identified transfer function in (14) is used to obtain theoptimal control gains for designed position controllers byusing MATLABSimulink
In addition the dynamics characteristic of the BLDCmotor with controller is also investigated by using SCMThetransfer function of the BLDC motor with controller can besimplified to a second-order linear system as described in(12) Figure 7 shows bode plot of the actual BLDC motorwith controllerThe bandwidth of the actual open loop BLDCmotor with controller is about 400 rads The bandwidth ofthe BLDC motor with controller is 20 times larger than thatof hydraulic part of the EHA systemTherefore in this study
110
115
120
125
Experiment
Mag
nitu
de (d
B)
Frequency (Hz)100 101 102
Figure 7 Bode plots of the open-loop actual BLDC motor withcontroller system
we consider that the dynamics of BLDCmotorwith controlleris negligible because the motor dynamic is sufficiently fasterthan hydraulic part of the EHA Then the electric part ofthe EHA system is taking account of the motor gain 119870V andcurrent saturation is reflected in the controller design and thecomputer simulations stage
4 Position Controller Design fora Prototype EHA
In this study an EHA prototype is developed for appli-cation in the industrial fields As mentioned in Section 2performance characteristics such as no overshoot and rapidresponse time in position control are the typical demandsof the EHA for industrial use Therefore appropriate control
The Scientific World Journal 7
Positioncontroller
BLDC motor with controller
Hydraulic part of EHA system
Motorcontroller
r e
120596
e xi
Ks
Km
Tm 120596p
plusmn100A
minus+ minus+
rpmplusmn10000Reference position (xd) 1
Jms + Bm
x(s)
120596p(s)=
ADp120573e
e
MV0
s3 + ((BM) + (CTDp120573eV0))s2 + (120573 (BCTDp + A2)MV0)s
Figure 8 Block diagram for the position control system of the EHA
strategy should be applied to EHA position control system inorder to achieve these outcomes
Figure 8 shows the block diagram of position controlsystem of the EHA As mentioned in the previous section inFigure 8 the dynamics of the BLDC motor with controlleris considered as just the motor gain 119870
119898
and saturation ofcurrent of the BLDC motor is considered as an actuatorconstraint
In order to compare and show the desirable performancecharacteristics for the proposed EHA control system threekinds of position controllers are designed based on identifiedsimple transfer function First an optimal PID controller isdesigned and applied to the system in order to understandthe basic characteristics of EHA position control systemThe optimal antiwindup PID controller is then designed toreduce overshoot due to saturation of current in the electricmotor Finally an adaptive antiwindup PID sliding modecontroller is designed to obtain the desirable performanceand robustness against the effect of hardware saturation loaddisturbance and parameter variation
41 Optimal PID and Optimal Antiwindup PID ControlSystems An optimal PID position control system is designedto understand basic control performance of EHA prototypeAlso an optimal antiwindup PID control system for the EHAis designed to obtain desirable performance characteristicconsidering saturation in electric motor
The cost function is considered during the design ofthe optimal PID and optimal antiwindup PID controllers asfollows [25]
119869 (119870119901
119870119894
119870119889
) =
infin
sum
119905=0
(119910step (119905) minus 119910119889
step (119905)) (16)
where 119910119889step(119905) is the desired step response of the optimalPID and optimal antiwindup PID control systems and 119910step(119905)is the step response by the identified transfer function in(14)The optimal PID and optimal antiwindup PID controllerdesigns can be stated as
min119870
119901119870
119894119870
119889
119869 (119870119901
119870119894
119870119889
) (17)
where 119870119901
119870119894
and 119870119889
are the proportional integral anddifferential control gains respectively
There are many optimization algorithms in the opti-mization toolbox of MATLABSimulink The cost functionis given by (119870
119901
119870119894
119870119889
) And the gains of the optimal PIDand optimal antiwindup PID controllers 119870
119901
119870119894
and 119870119889
can be found by using the optimization toolbox of MAT-LABSimulink To find optimal control gains the referencestep input is applied in optimization process and the responseperformance is set as follows The amplitude of reference is20mm the rising time is 04 seconds settling time is 08seconds percent overshoot is under 5 and steady-stateerror is under 01mm
In the optimization process of optimal PID and optimalantiwindup PID controllers system parameter uncertaintiesdue to the modeling error are considered Specifically plusmn10ofmodeling error is considered in terms of identified transferfunction associate with variable system parameters such aseffective bulk modulus of the working fluid and total leakagecoefficient
With respect to optimal antiwindup PID and antiwindupPID sliding mode controllers the antiwindup algorithmshown in Figure 9 is used to consider saturation in an electricmotor [2 26ndash28]
Figure 10 shows the results of a computer simulationwith optimal antiwindup PID control gains using MAT-LABSimulink optimization toolbox based on identifiedtransfer function considering model uncertainty The dottedline there shows upper bound and lower bound consideringthe plusmn10 of modeling error and straight line shows nominalsimulation result with optimal antiwindup PID control gainsAs shown in Figure 10 the simulation result with optimalgains satisfies set response performance
42 Adaptive Antiwindup SlidingModeController Consideringthe PID Sliding Surface In this study the adaptive anti-windup PID sliding mode control scheme is also designedto achieve desirable performance and robustness of EHAposition control systems Throughout the controller designprocess the effective bulk modulus and leakage coefficientsare considered as variable systemparameters In order to con-sider saturation in electric motor the antiwindup algorithmpresented in Figure 8 also applies to the adaptive antiwindupPID sliding mode control scheme
8 The Scientific World Journal
Position controller BLDC motor with controller
Motorcontroller
r i re
120596
i
Ks
Ks Km
Tm
plusmn100A
minus+
+++
+
rpmplusmn10000
minus
ka
ei
s
k2s
orKi
s
k3 or Kd
k1 or Kpe 120596p1
Jms + Bm
Figure 9 Block diagram for adopted antiwindup algorithm in controller design
06 07 08 09 1 1118
19
20
21
22Upper boundary
Lower boundary
Nominal response
0 02 04 06 08 1 12 14 16 18 20
5
10
15
20
25
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
Figure 10 Step response of the optimal antiwindup PID controlsystem in computer simulation based on identified transfer functionof EHA system
The PID sliding surface 120577 for the design of the adaptivesliding mode control system is defined as [29ndash32]
120577 = 1198961
119890 + 1198962
int 119890 119889119905 + 1198963
119890 (18)
where the tracking error of the position 119890 = 119909119889
minus 119909 119909 isthe displacement of hydraulic cylinder and 119896
1
1198962
and 1198963
arepositive design parameters
The sliding mode control law consists of equivalent androbust control term that is
120596119901
= 120596119901119890119902
+ 120596119901robust (19)
By combining (11) and (18) with consideration of the noiseterm in the jerk =
119898
+ 119899
the derivative of the slidingsurface 120577 can be written as
120577 = minus 1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
120596119901
+ 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119898
+ 119899
)
+ 1198963
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+ 1198963
119889
+ 1198961
119890 + 1198962
119890
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891
(20)
where 119891 = 1198911
+ (119862119879
119860)1198912
+ (1198810
119860119863119901
120573119890
) 1198912
is lumped uncer-tain nonlinearities of the EHA system and the subscripts 119898and 119899 denote the nominal and noisy values respectively
To determine the equivalent control term 120596119901119890119902
the noiseterm in the jerk is neglected and it is assumed that the slidingsurface 120577 is at steady-state that is 120577 = 0 and then theequivalent control law can be determined as
120596119901119890119902
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119889
(21)
Thus 120577 can be rewritten as
120577 = 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119899
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891 (22)
In the standard sliding mode control to satisfy the reach-ability condition that directs system trajectories toward asliding surface where they remain and to attenuate chatteringin the control input the derivative of the sliding surface isselected as [33 34]
120577 = minus119863120577 minus 119870 sgn (120577) (23)
where119863 and119870 are positive design parameters
The Scientific World Journal 9
To determine a robust control term120596119901robust that achieves
robustness to uncertainties such as noise terms in the jerk andunmodeled system dynamics as well as the disturbance forceit is assumed that
1198630
10038161003816100381610038161205771003816100381610038161003816 + 1198700 gt
100381610038161003816100381610038161003816100381610038161003816
1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119899
+1
1198721198810
119891)
100381610038161003816100381610038161003816100381610038161003816
+ 120578
(24)
where 1198700
= (119860119863119901
120573119890
(1198611198810
+ 119862119879
119863119901
119872120573119890
))119870 and 1198630
=
(119860119863119901
120573119890
(1198611198810
+119862119879
119863119901
119872120573119890
))119863 are positive design parametersand 120578 is sufficiently small positive parameter On the assump-tion of (24) the robust control law is determined as
120596119901robust = 119863120577 + 119870 sgn (120577) (25)
Finally the sliding mode control law is selected as
120596119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 119889
+1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119863120577 + 119870 sgn (120577)
(26)
If the total leakage coefficient 119862119879
and the effective bulkmodulus of EHA systems 120573
119890
are considered as variableparameters that is 119862
119879
= 119862119879119899
+ 119862119879119901
and 120573119890
= 120573119890119899
+ 120573119890119901
then the uncertainty 120595 is defined as
120595 = 120579119879
120593 = (1198721198810
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
) 119898
+ (
(1198602
+ 119861119862119879119901
119863119901
) 120573119890119901
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)
(27)
where 120579119879
= [(1198721198810
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)) ((1198602
+
119861119862119879119901
119863119901
)120573119890119901
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
))] and 120593 = [119909
119898
119909
] Theparameter vector 120579 is considered as an unknown parametervector and it can be estimated by using the update lawFrom (26) and estimated unknown parameter vector 120579 theestimated sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119860119863119901
120573119890119899
times 119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
+ 119863120577 + 119870 sgn (120577)
(28)
In order to obtain the update law for the unknownparameters the Lyapunov candidate is defined as
119881 =1
21205772
+1
2120574120579119879
120579 (29)
where 120579 = 120579 minus 120579 120574 is a positive parameter Also 120579 and 120579 arethe nominal and estimated parameter vectors respectivelyThe derivative of the Lyapunov candidate including slidingdynamics is expressed as
= 120577 [119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
minus1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
119901
] minus1
120574120579119879120579
(30)
Substituting the estimated angular velocity of the pump 119901
given by (28) into (30) yields
= minus1198631205772
minus 119870120577 sgn (120577) + 120579119879 (120577120593 minus 1120574
120579) (31)
From the derivative of the Lyapunov included sliding dynam-ics the update law for the unknown parameters is selected as
120579 = 120574120577120593 (32)
Therefore the derivative of the Lyapunov is given as
= minus1198631205772
minus 119870120577 sgn (120577) le 0 (33)
By applying invariant set theorem for (33) the asymptoticalstability of the EHAposition control system is guaranteed [3334]
Finally the sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times (120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890)
+ 119863120577 + 119870 sgn (120577) (34)
where 120573119890
(119905 + 119879119904
) = (119889120573119890
(119905)119889119905)119879119904
+ 120573119890
(119905) 119862119879
(119905 + 119879119904
) =
(119889119862119879
(119905)119889119905)119879119904
+ 119862119879
(119905) and 119879119904
is the sampling time
10 The Scientific World Journal
Table 3 Optimal gains of optimal PID antiwindup PID and adaptive anti-windup PID sliding mode control systems in experiments
Gain Optimal PID Optimal antiwindup PID Adaptive antiwindup PID sliding modeProportional (119870
119901
or 1198961
) 10343 16947 950Integral (119870
119894
or 1198962
) 184 10877 0001Derivative (119870
119889
or 1198963
) 47 4160 145Antiwindup (119870
119886
) mdash 0001 0001
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 11 Performances of optimal PID position control system for EHA without load disturbance (only mass load is applied)
5 Experimental Results and Discussion
This section looks to the experimental results in order tocompare the performance of a position control systemsThreekinds of controllers are compared in order to show improvedperformance of overshoot reduction and robustness to theparameter change and load disturbance of the proposedcontroller for EHA position control system
Firstly optimal PID controller is designed and imple-mented by experiments Figure 11 shows experimental resultsof the PID position controller with step references of fourdifferent amplitudes which are 10 20 30 and 40mmwithoutload disturbance that is only mass load is applied as load tothe position control system
The gains of the three-position controllers are optimallyselected by using MATLABSimulink optimization toolboxbased on identified system dynamic model of (14) In theprocess of optimal gain selection the amplitude of positionreference is set to 20mm and target performance is 04seconds of the rising time 08 seconds of settling timeunder 5 of percent overshoot and under 01mm of steady-state error In experiments the optimal gains derived fromMATLABSimulink optimization toolbox are tuned to obtainbest responses The finally tuned optimal gains of the threecontrollers are represented in Table 3
As shown in Figure 11 large overshoot is observed inposition control result for using the optimal PID positioncontroller The performance of optimal PID position control
system is represented in Table 4The performance of optimalPID controller in experiment is not satisfactory the aimedvalue In detail large overshoot is observed in experimentsThe current and angular velocity saturations of BLDC motorin position experiment result of optimal PID controller areshown in Figure 12The large overshoot in position controllercan be caused due to saturation of BLDC motor as shown inFigure 12
To reduce such a large overshoot an antiwindup algo-rithmwhich is described in Figure 9 is applied to the positioncontrol system of the EHA The performance characteristicsof an antiwindup PID position controller are depicted inFigure 13 and also the values of performance indices areshown in Table 4 As shown in Figure 13 the overshoot ofthe optimal antiwindup PID controller is more diminishedthan that of the optimal PID controller However as shown inTable 4 the antiwindupPID controller still has a performanceof relatively long settling times which do not meet the aimedperformance Moreover as the amplitude of the referenceinput increases the steady-state error is increasing as shownin Figure 13
Figure 14 shows the experimental results of optimal adap-tive antiwindup sliding mode position control system for theEHA system As shown in Figure 14 the optimal antiwindupPID sliding mode position control system has a better per-formance than the system with optimal PID and antiwindupPID controllers such that relatively small overshoot and shortsettling time are obtained by the adaptive antiwindup PID
The Scientific World Journal 11
Table 4 Comparison of the performance of optimal PID optimal antiwindup PID and adaptive antiwindup PID sliding mode controlsystems without load disturbance
Performance Reference Optimal PID Optimal antiwindup PID Adaptive antiwindup PIDsliding mode
Overshoot
10mm 389 208 1020mm 161 133 0530mm 147 119 0240mm 122 82 01
Settling time
10mm 178 sec 22 sec 06 sec20mm 056 sec 22 sec 06 sec30mm 058 sec 063 sec 07 sec40mm 069 sec 26 sec 07 sec
0 05 1 15 2 25 3minus120
minus90
minus60
minus30
0
30
60
90
120
150
Impr
esse
d cu
rren
t (A
)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(a) Saturation of impressed current
0 05 1 15 2 25 3minus6000
minus4000
minus2000
0
2000
4000
6000
8000
10000
12000
14000
Mot
or an
gula
r spe
ed (r
pm)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Saturation of angular velocity
Figure 12 Saturation of BLDCmotor for optimal PID position control system for EHAwithout load disturbance (only mass load is applied)
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 13 Performances of optimal antiwindup PID position control system for EHA without load disturbance (only mass load is applied)
12 The Scientific World Journal
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 14 Performances of optimal adaptive antiwindup PID sliding mode position control system for EHA without load disturbance (onlymass load is applied)
0 05 1 15 2 25 30
1
2
3
4
5
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 15 Pressure variations of optimal PID position control system for EHA without load disturbance (only mass load is applied)
sliding mode control system As shown in Figure 14 andTable 4 the consistent performance is realized by the optimaladaptive antiwindup PID sliding mode control system Thetime-domain quantitative performance indicators are alsosummarized in Table 4 for optimal adaptive antiwindup PIDsliding mode control system without load
On the other hand Figure 15 depicts pressure variationsof the optimal PID EHAposition control systemwithout loaddisturbance As shown in Figure 15 the range of operatingpressure of the EHA system is under 3MPa inwhich the effec-tive bulk modulus can be significantly changed according tocontained air ratio of working fluid [5 7 11ndash13] as shownin Figure 16 The range of operating pressure for antiwindup
PID and antiwindup PID sliding mode control system is alsounder 3MPa
Figure 17 depicts pressures of the EHA system when theposition control systems are operating with load disturbanceAs shown in Figure 17 the maximum operating pressures ofthe EHA system is about 10MPa when the position controlsystems are working under the condition of adding distur-bance loadThemaximumoperating pressure for antiwindupPID and antiwindup PID sliding mode control system isalso up to 10MPa Thus the effective bulk modulus can bechanged greatly according to variation of operating pressureof the EHA systems In addition total leakage coefficient alsocan be changed in response to the level of working pressure
The Scientific World Journal 13
0 5 10 15 20 25 300
400
800
1200
1600
2000
Bulk
mod
ulus
(MPa
)
Pressure (MPa)
Contained air ratio ()001
110
Figure 16 Example of the relationship between pressure and effective bulk modulus [12 13]
0 05 1 15 2 25 30123456789
101112
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 17 Pressure variations of optimal PID position control system for EHA with load disturbance
In order to investigate robustness to the lumped systemuncertainties such as varying parameters and modeling errorand load disturbance the performances of the three-positioncontrollers of EHA system are compared in experiments byapplying load disturbance The experiments are conductedwith 20mm position reference and the load disturbance isapplied by controlling the opening area of servo valve whichis installed in a meter outline of load cylinder
As shown in Figure 18 the optimal PID and optimalantiwindup PID control systems do not achieve robustnessto the parameter change and load disturbance In spite of theload disturbance and saturation of the BLDC motor in theposition control system for EHA the adaptive antiwindupPID sliding mode control system has a better performanceand robustness than the optimal PID and optimal antiwindupPID control systems such that the adaptive antiwindup PID
sliding mode control system recovers the parameter changeand external disturbance in about 09 sec with a small over-shootThe time-domain quantitative performance indicatorsare summarized in Table 5 for optimal PID antiwindup PIDand adaptive antiwindup PID sliding mode control systemswith load disturbance The list of terms are represented inTable 6
6 Conclusion
This paper discussed the application of the optimal PIDcontroller with optimal control gains using the optimizationtoolbox ofMATLABSimulink to the position control systemof EHA in order to understand the basic performancecharacteristics of the system In experiment with optimal PIDcontroller large overshoot due to saturation of electric motoris observed
14 The Scientific World Journal
0 05 1 15 2 25 30
5
10
15
20
25
30
35
Position referenceOptimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(b) Position errors
0 05 1 15 2 25 30
2
4
6
8
10
Load
forc
e (kN
)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(c) Load force
Figure 18 Performances of optimal PID antiwindup PID and adaptive antiwindup PID sliding mode control systems for EHA with loaddisturbance
Table 5 Comparison of the performance of optimal PID optimalantiwindup PID and adaptive antiwindup PID slidingmode controlsystems with load disturbance
Performance OptimalPID
Optimalantiwindup PID
Adaptive antiwindupPID sliding mode
Overshoot 45 39 12Settling time 38 sec 18 sec 08 sec
In order to achieve the desirable performance of EHAposition control system optimal antiwindup PID controller
and adaptive antiwindup PID sliding mode controller arealso applied to control the position of EHA systems Inthe process of robust control system design mathematicalmodeling was carried out based on theoretical analysisand the simple third-order nominal model was derivedThe system parameters of the simple second-order nominalmodel were identified by the signal compression method
Based on the experimental results and the time-domainquantitative performance indicators the performance of theEHA position control system can be improved and robustto the load disturbance parameter variation and system
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
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![Page 6: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/6.jpg)
6 The Scientific World Journal
0 1 2 3 4 5 6 7 8minus3
minus25minus2
minus15minus1
minus050
051
152
253
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
ExperimentModel
(a) Response for the test signal
0 05 1 15 2 25 3 35 4 45
0
2
4
6
8
10
12
14
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
minus2
ExperimentModel
(b) Step response
Figure 6 Time responses of the position control system obtained by the experiment and nominal model
After eliminating the effect of the proportional controllerthe identified transfer function of the hydraulic part of theEHA prototype is as follows
119866 (119904) =118 times 10
4
1199043
+ 22311199042
+ 718 times 105
119904 (14)
The identified system parameters were verified on thetime domain Figures 6(a) and 6(b) show the responseagainst test signal and the step responses of the nominalmodel and actual system respectively The validations ofthe identified parameters are estimated quantitatively by thecross-correlation as shown in [24]
Corr =sum119873
119896=1
(119884119901
(119896) minus 119884119901
) (119884119898
(119896) minus 119884119898
)
radicsum119873
119896=1
(119884119901
(119896) minus 119884119901
)radicsum119873
119896=1
(119884119898
(119896) minus 119884119898
)2
(15)
where 119884119901
(119896) and 119884119898
(119896) are the responses of the real andnominal model in time train 119896 respectively 119884
119901
and 119884119898
arethe mean values of 119884
119901
(119896) and 119884119898
(119896) 119873 is the acquired datanumberThe value of the cross-correlation is 0904 which canbe calculated from the identification results The identifiedsystem parameters are then available to controller designThe identified transfer function in (14) is used to obtain theoptimal control gains for designed position controllers byusing MATLABSimulink
In addition the dynamics characteristic of the BLDCmotor with controller is also investigated by using SCMThetransfer function of the BLDC motor with controller can besimplified to a second-order linear system as described in(12) Figure 7 shows bode plot of the actual BLDC motorwith controllerThe bandwidth of the actual open loop BLDCmotor with controller is about 400 rads The bandwidth ofthe BLDC motor with controller is 20 times larger than thatof hydraulic part of the EHA systemTherefore in this study
110
115
120
125
Experiment
Mag
nitu
de (d
B)
Frequency (Hz)100 101 102
Figure 7 Bode plots of the open-loop actual BLDC motor withcontroller system
we consider that the dynamics of BLDCmotorwith controlleris negligible because the motor dynamic is sufficiently fasterthan hydraulic part of the EHA Then the electric part ofthe EHA system is taking account of the motor gain 119870V andcurrent saturation is reflected in the controller design and thecomputer simulations stage
4 Position Controller Design fora Prototype EHA
In this study an EHA prototype is developed for appli-cation in the industrial fields As mentioned in Section 2performance characteristics such as no overshoot and rapidresponse time in position control are the typical demandsof the EHA for industrial use Therefore appropriate control
The Scientific World Journal 7
Positioncontroller
BLDC motor with controller
Hydraulic part of EHA system
Motorcontroller
r e
120596
e xi
Ks
Km
Tm 120596p
plusmn100A
minus+ minus+
rpmplusmn10000Reference position (xd) 1
Jms + Bm
x(s)
120596p(s)=
ADp120573e
e
MV0
s3 + ((BM) + (CTDp120573eV0))s2 + (120573 (BCTDp + A2)MV0)s
Figure 8 Block diagram for the position control system of the EHA
strategy should be applied to EHA position control system inorder to achieve these outcomes
Figure 8 shows the block diagram of position controlsystem of the EHA As mentioned in the previous section inFigure 8 the dynamics of the BLDC motor with controlleris considered as just the motor gain 119870
119898
and saturation ofcurrent of the BLDC motor is considered as an actuatorconstraint
In order to compare and show the desirable performancecharacteristics for the proposed EHA control system threekinds of position controllers are designed based on identifiedsimple transfer function First an optimal PID controller isdesigned and applied to the system in order to understandthe basic characteristics of EHA position control systemThe optimal antiwindup PID controller is then designed toreduce overshoot due to saturation of current in the electricmotor Finally an adaptive antiwindup PID sliding modecontroller is designed to obtain the desirable performanceand robustness against the effect of hardware saturation loaddisturbance and parameter variation
41 Optimal PID and Optimal Antiwindup PID ControlSystems An optimal PID position control system is designedto understand basic control performance of EHA prototypeAlso an optimal antiwindup PID control system for the EHAis designed to obtain desirable performance characteristicconsidering saturation in electric motor
The cost function is considered during the design ofthe optimal PID and optimal antiwindup PID controllers asfollows [25]
119869 (119870119901
119870119894
119870119889
) =
infin
sum
119905=0
(119910step (119905) minus 119910119889
step (119905)) (16)
where 119910119889step(119905) is the desired step response of the optimalPID and optimal antiwindup PID control systems and 119910step(119905)is the step response by the identified transfer function in(14)The optimal PID and optimal antiwindup PID controllerdesigns can be stated as
min119870
119901119870
119894119870
119889
119869 (119870119901
119870119894
119870119889
) (17)
where 119870119901
119870119894
and 119870119889
are the proportional integral anddifferential control gains respectively
There are many optimization algorithms in the opti-mization toolbox of MATLABSimulink The cost functionis given by (119870
119901
119870119894
119870119889
) And the gains of the optimal PIDand optimal antiwindup PID controllers 119870
119901
119870119894
and 119870119889
can be found by using the optimization toolbox of MAT-LABSimulink To find optimal control gains the referencestep input is applied in optimization process and the responseperformance is set as follows The amplitude of reference is20mm the rising time is 04 seconds settling time is 08seconds percent overshoot is under 5 and steady-stateerror is under 01mm
In the optimization process of optimal PID and optimalantiwindup PID controllers system parameter uncertaintiesdue to the modeling error are considered Specifically plusmn10ofmodeling error is considered in terms of identified transferfunction associate with variable system parameters such aseffective bulk modulus of the working fluid and total leakagecoefficient
With respect to optimal antiwindup PID and antiwindupPID sliding mode controllers the antiwindup algorithmshown in Figure 9 is used to consider saturation in an electricmotor [2 26ndash28]
Figure 10 shows the results of a computer simulationwith optimal antiwindup PID control gains using MAT-LABSimulink optimization toolbox based on identifiedtransfer function considering model uncertainty The dottedline there shows upper bound and lower bound consideringthe plusmn10 of modeling error and straight line shows nominalsimulation result with optimal antiwindup PID control gainsAs shown in Figure 10 the simulation result with optimalgains satisfies set response performance
42 Adaptive Antiwindup SlidingModeController Consideringthe PID Sliding Surface In this study the adaptive anti-windup PID sliding mode control scheme is also designedto achieve desirable performance and robustness of EHAposition control systems Throughout the controller designprocess the effective bulk modulus and leakage coefficientsare considered as variable systemparameters In order to con-sider saturation in electric motor the antiwindup algorithmpresented in Figure 8 also applies to the adaptive antiwindupPID sliding mode control scheme
8 The Scientific World Journal
Position controller BLDC motor with controller
Motorcontroller
r i re
120596
i
Ks
Ks Km
Tm
plusmn100A
minus+
+++
+
rpmplusmn10000
minus
ka
ei
s
k2s
orKi
s
k3 or Kd
k1 or Kpe 120596p1
Jms + Bm
Figure 9 Block diagram for adopted antiwindup algorithm in controller design
06 07 08 09 1 1118
19
20
21
22Upper boundary
Lower boundary
Nominal response
0 02 04 06 08 1 12 14 16 18 20
5
10
15
20
25
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
Figure 10 Step response of the optimal antiwindup PID controlsystem in computer simulation based on identified transfer functionof EHA system
The PID sliding surface 120577 for the design of the adaptivesliding mode control system is defined as [29ndash32]
120577 = 1198961
119890 + 1198962
int 119890 119889119905 + 1198963
119890 (18)
where the tracking error of the position 119890 = 119909119889
minus 119909 119909 isthe displacement of hydraulic cylinder and 119896
1
1198962
and 1198963
arepositive design parameters
The sliding mode control law consists of equivalent androbust control term that is
120596119901
= 120596119901119890119902
+ 120596119901robust (19)
By combining (11) and (18) with consideration of the noiseterm in the jerk =
119898
+ 119899
the derivative of the slidingsurface 120577 can be written as
120577 = minus 1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
120596119901
+ 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119898
+ 119899
)
+ 1198963
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+ 1198963
119889
+ 1198961
119890 + 1198962
119890
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891
(20)
where 119891 = 1198911
+ (119862119879
119860)1198912
+ (1198810
119860119863119901
120573119890
) 1198912
is lumped uncer-tain nonlinearities of the EHA system and the subscripts 119898and 119899 denote the nominal and noisy values respectively
To determine the equivalent control term 120596119901119890119902
the noiseterm in the jerk is neglected and it is assumed that the slidingsurface 120577 is at steady-state that is 120577 = 0 and then theequivalent control law can be determined as
120596119901119890119902
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119889
(21)
Thus 120577 can be rewritten as
120577 = 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119899
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891 (22)
In the standard sliding mode control to satisfy the reach-ability condition that directs system trajectories toward asliding surface where they remain and to attenuate chatteringin the control input the derivative of the sliding surface isselected as [33 34]
120577 = minus119863120577 minus 119870 sgn (120577) (23)
where119863 and119870 are positive design parameters
The Scientific World Journal 9
To determine a robust control term120596119901robust that achieves
robustness to uncertainties such as noise terms in the jerk andunmodeled system dynamics as well as the disturbance forceit is assumed that
1198630
10038161003816100381610038161205771003816100381610038161003816 + 1198700 gt
100381610038161003816100381610038161003816100381610038161003816
1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119899
+1
1198721198810
119891)
100381610038161003816100381610038161003816100381610038161003816
+ 120578
(24)
where 1198700
= (119860119863119901
120573119890
(1198611198810
+ 119862119879
119863119901
119872120573119890
))119870 and 1198630
=
(119860119863119901
120573119890
(1198611198810
+119862119879
119863119901
119872120573119890
))119863 are positive design parametersand 120578 is sufficiently small positive parameter On the assump-tion of (24) the robust control law is determined as
120596119901robust = 119863120577 + 119870 sgn (120577) (25)
Finally the sliding mode control law is selected as
120596119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 119889
+1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119863120577 + 119870 sgn (120577)
(26)
If the total leakage coefficient 119862119879
and the effective bulkmodulus of EHA systems 120573
119890
are considered as variableparameters that is 119862
119879
= 119862119879119899
+ 119862119879119901
and 120573119890
= 120573119890119899
+ 120573119890119901
then the uncertainty 120595 is defined as
120595 = 120579119879
120593 = (1198721198810
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
) 119898
+ (
(1198602
+ 119861119862119879119901
119863119901
) 120573119890119901
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)
(27)
where 120579119879
= [(1198721198810
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)) ((1198602
+
119861119862119879119901
119863119901
)120573119890119901
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
))] and 120593 = [119909
119898
119909
] Theparameter vector 120579 is considered as an unknown parametervector and it can be estimated by using the update lawFrom (26) and estimated unknown parameter vector 120579 theestimated sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119860119863119901
120573119890119899
times 119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
+ 119863120577 + 119870 sgn (120577)
(28)
In order to obtain the update law for the unknownparameters the Lyapunov candidate is defined as
119881 =1
21205772
+1
2120574120579119879
120579 (29)
where 120579 = 120579 minus 120579 120574 is a positive parameter Also 120579 and 120579 arethe nominal and estimated parameter vectors respectivelyThe derivative of the Lyapunov candidate including slidingdynamics is expressed as
= 120577 [119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
minus1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
119901
] minus1
120574120579119879120579
(30)
Substituting the estimated angular velocity of the pump 119901
given by (28) into (30) yields
= minus1198631205772
minus 119870120577 sgn (120577) + 120579119879 (120577120593 minus 1120574
120579) (31)
From the derivative of the Lyapunov included sliding dynam-ics the update law for the unknown parameters is selected as
120579 = 120574120577120593 (32)
Therefore the derivative of the Lyapunov is given as
= minus1198631205772
minus 119870120577 sgn (120577) le 0 (33)
By applying invariant set theorem for (33) the asymptoticalstability of the EHAposition control system is guaranteed [3334]
Finally the sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times (120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890)
+ 119863120577 + 119870 sgn (120577) (34)
where 120573119890
(119905 + 119879119904
) = (119889120573119890
(119905)119889119905)119879119904
+ 120573119890
(119905) 119862119879
(119905 + 119879119904
) =
(119889119862119879
(119905)119889119905)119879119904
+ 119862119879
(119905) and 119879119904
is the sampling time
10 The Scientific World Journal
Table 3 Optimal gains of optimal PID antiwindup PID and adaptive anti-windup PID sliding mode control systems in experiments
Gain Optimal PID Optimal antiwindup PID Adaptive antiwindup PID sliding modeProportional (119870
119901
or 1198961
) 10343 16947 950Integral (119870
119894
or 1198962
) 184 10877 0001Derivative (119870
119889
or 1198963
) 47 4160 145Antiwindup (119870
119886
) mdash 0001 0001
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 11 Performances of optimal PID position control system for EHA without load disturbance (only mass load is applied)
5 Experimental Results and Discussion
This section looks to the experimental results in order tocompare the performance of a position control systemsThreekinds of controllers are compared in order to show improvedperformance of overshoot reduction and robustness to theparameter change and load disturbance of the proposedcontroller for EHA position control system
Firstly optimal PID controller is designed and imple-mented by experiments Figure 11 shows experimental resultsof the PID position controller with step references of fourdifferent amplitudes which are 10 20 30 and 40mmwithoutload disturbance that is only mass load is applied as load tothe position control system
The gains of the three-position controllers are optimallyselected by using MATLABSimulink optimization toolboxbased on identified system dynamic model of (14) In theprocess of optimal gain selection the amplitude of positionreference is set to 20mm and target performance is 04seconds of the rising time 08 seconds of settling timeunder 5 of percent overshoot and under 01mm of steady-state error In experiments the optimal gains derived fromMATLABSimulink optimization toolbox are tuned to obtainbest responses The finally tuned optimal gains of the threecontrollers are represented in Table 3
As shown in Figure 11 large overshoot is observed inposition control result for using the optimal PID positioncontroller The performance of optimal PID position control
system is represented in Table 4The performance of optimalPID controller in experiment is not satisfactory the aimedvalue In detail large overshoot is observed in experimentsThe current and angular velocity saturations of BLDC motorin position experiment result of optimal PID controller areshown in Figure 12The large overshoot in position controllercan be caused due to saturation of BLDC motor as shown inFigure 12
To reduce such a large overshoot an antiwindup algo-rithmwhich is described in Figure 9 is applied to the positioncontrol system of the EHA The performance characteristicsof an antiwindup PID position controller are depicted inFigure 13 and also the values of performance indices areshown in Table 4 As shown in Figure 13 the overshoot ofthe optimal antiwindup PID controller is more diminishedthan that of the optimal PID controller However as shown inTable 4 the antiwindupPID controller still has a performanceof relatively long settling times which do not meet the aimedperformance Moreover as the amplitude of the referenceinput increases the steady-state error is increasing as shownin Figure 13
Figure 14 shows the experimental results of optimal adap-tive antiwindup sliding mode position control system for theEHA system As shown in Figure 14 the optimal antiwindupPID sliding mode position control system has a better per-formance than the system with optimal PID and antiwindupPID controllers such that relatively small overshoot and shortsettling time are obtained by the adaptive antiwindup PID
The Scientific World Journal 11
Table 4 Comparison of the performance of optimal PID optimal antiwindup PID and adaptive antiwindup PID sliding mode controlsystems without load disturbance
Performance Reference Optimal PID Optimal antiwindup PID Adaptive antiwindup PIDsliding mode
Overshoot
10mm 389 208 1020mm 161 133 0530mm 147 119 0240mm 122 82 01
Settling time
10mm 178 sec 22 sec 06 sec20mm 056 sec 22 sec 06 sec30mm 058 sec 063 sec 07 sec40mm 069 sec 26 sec 07 sec
0 05 1 15 2 25 3minus120
minus90
minus60
minus30
0
30
60
90
120
150
Impr
esse
d cu
rren
t (A
)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(a) Saturation of impressed current
0 05 1 15 2 25 3minus6000
minus4000
minus2000
0
2000
4000
6000
8000
10000
12000
14000
Mot
or an
gula
r spe
ed (r
pm)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Saturation of angular velocity
Figure 12 Saturation of BLDCmotor for optimal PID position control system for EHAwithout load disturbance (only mass load is applied)
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 13 Performances of optimal antiwindup PID position control system for EHA without load disturbance (only mass load is applied)
12 The Scientific World Journal
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 14 Performances of optimal adaptive antiwindup PID sliding mode position control system for EHA without load disturbance (onlymass load is applied)
0 05 1 15 2 25 30
1
2
3
4
5
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 15 Pressure variations of optimal PID position control system for EHA without load disturbance (only mass load is applied)
sliding mode control system As shown in Figure 14 andTable 4 the consistent performance is realized by the optimaladaptive antiwindup PID sliding mode control system Thetime-domain quantitative performance indicators are alsosummarized in Table 4 for optimal adaptive antiwindup PIDsliding mode control system without load
On the other hand Figure 15 depicts pressure variationsof the optimal PID EHAposition control systemwithout loaddisturbance As shown in Figure 15 the range of operatingpressure of the EHA system is under 3MPa inwhich the effec-tive bulk modulus can be significantly changed according tocontained air ratio of working fluid [5 7 11ndash13] as shownin Figure 16 The range of operating pressure for antiwindup
PID and antiwindup PID sliding mode control system is alsounder 3MPa
Figure 17 depicts pressures of the EHA system when theposition control systems are operating with load disturbanceAs shown in Figure 17 the maximum operating pressures ofthe EHA system is about 10MPa when the position controlsystems are working under the condition of adding distur-bance loadThemaximumoperating pressure for antiwindupPID and antiwindup PID sliding mode control system isalso up to 10MPa Thus the effective bulk modulus can bechanged greatly according to variation of operating pressureof the EHA systems In addition total leakage coefficient alsocan be changed in response to the level of working pressure
The Scientific World Journal 13
0 5 10 15 20 25 300
400
800
1200
1600
2000
Bulk
mod
ulus
(MPa
)
Pressure (MPa)
Contained air ratio ()001
110
Figure 16 Example of the relationship between pressure and effective bulk modulus [12 13]
0 05 1 15 2 25 30123456789
101112
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 17 Pressure variations of optimal PID position control system for EHA with load disturbance
In order to investigate robustness to the lumped systemuncertainties such as varying parameters and modeling errorand load disturbance the performances of the three-positioncontrollers of EHA system are compared in experiments byapplying load disturbance The experiments are conductedwith 20mm position reference and the load disturbance isapplied by controlling the opening area of servo valve whichis installed in a meter outline of load cylinder
As shown in Figure 18 the optimal PID and optimalantiwindup PID control systems do not achieve robustnessto the parameter change and load disturbance In spite of theload disturbance and saturation of the BLDC motor in theposition control system for EHA the adaptive antiwindupPID sliding mode control system has a better performanceand robustness than the optimal PID and optimal antiwindupPID control systems such that the adaptive antiwindup PID
sliding mode control system recovers the parameter changeand external disturbance in about 09 sec with a small over-shootThe time-domain quantitative performance indicatorsare summarized in Table 5 for optimal PID antiwindup PIDand adaptive antiwindup PID sliding mode control systemswith load disturbance The list of terms are represented inTable 6
6 Conclusion
This paper discussed the application of the optimal PIDcontroller with optimal control gains using the optimizationtoolbox ofMATLABSimulink to the position control systemof EHA in order to understand the basic performancecharacteristics of the system In experiment with optimal PIDcontroller large overshoot due to saturation of electric motoris observed
14 The Scientific World Journal
0 05 1 15 2 25 30
5
10
15
20
25
30
35
Position referenceOptimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(b) Position errors
0 05 1 15 2 25 30
2
4
6
8
10
Load
forc
e (kN
)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(c) Load force
Figure 18 Performances of optimal PID antiwindup PID and adaptive antiwindup PID sliding mode control systems for EHA with loaddisturbance
Table 5 Comparison of the performance of optimal PID optimalantiwindup PID and adaptive antiwindup PID slidingmode controlsystems with load disturbance
Performance OptimalPID
Optimalantiwindup PID
Adaptive antiwindupPID sliding mode
Overshoot 45 39 12Settling time 38 sec 18 sec 08 sec
In order to achieve the desirable performance of EHAposition control system optimal antiwindup PID controller
and adaptive antiwindup PID sliding mode controller arealso applied to control the position of EHA systems Inthe process of robust control system design mathematicalmodeling was carried out based on theoretical analysisand the simple third-order nominal model was derivedThe system parameters of the simple second-order nominalmodel were identified by the signal compression method
Based on the experimental results and the time-domainquantitative performance indicators the performance of theEHA position control system can be improved and robustto the load disturbance parameter variation and system
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
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International Journal of
![Page 7: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/7.jpg)
The Scientific World Journal 7
Positioncontroller
BLDC motor with controller
Hydraulic part of EHA system
Motorcontroller
r e
120596
e xi
Ks
Km
Tm 120596p
plusmn100A
minus+ minus+
rpmplusmn10000Reference position (xd) 1
Jms + Bm
x(s)
120596p(s)=
ADp120573e
e
MV0
s3 + ((BM) + (CTDp120573eV0))s2 + (120573 (BCTDp + A2)MV0)s
Figure 8 Block diagram for the position control system of the EHA
strategy should be applied to EHA position control system inorder to achieve these outcomes
Figure 8 shows the block diagram of position controlsystem of the EHA As mentioned in the previous section inFigure 8 the dynamics of the BLDC motor with controlleris considered as just the motor gain 119870
119898
and saturation ofcurrent of the BLDC motor is considered as an actuatorconstraint
In order to compare and show the desirable performancecharacteristics for the proposed EHA control system threekinds of position controllers are designed based on identifiedsimple transfer function First an optimal PID controller isdesigned and applied to the system in order to understandthe basic characteristics of EHA position control systemThe optimal antiwindup PID controller is then designed toreduce overshoot due to saturation of current in the electricmotor Finally an adaptive antiwindup PID sliding modecontroller is designed to obtain the desirable performanceand robustness against the effect of hardware saturation loaddisturbance and parameter variation
41 Optimal PID and Optimal Antiwindup PID ControlSystems An optimal PID position control system is designedto understand basic control performance of EHA prototypeAlso an optimal antiwindup PID control system for the EHAis designed to obtain desirable performance characteristicconsidering saturation in electric motor
The cost function is considered during the design ofthe optimal PID and optimal antiwindup PID controllers asfollows [25]
119869 (119870119901
119870119894
119870119889
) =
infin
sum
119905=0
(119910step (119905) minus 119910119889
step (119905)) (16)
where 119910119889step(119905) is the desired step response of the optimalPID and optimal antiwindup PID control systems and 119910step(119905)is the step response by the identified transfer function in(14)The optimal PID and optimal antiwindup PID controllerdesigns can be stated as
min119870
119901119870
119894119870
119889
119869 (119870119901
119870119894
119870119889
) (17)
where 119870119901
119870119894
and 119870119889
are the proportional integral anddifferential control gains respectively
There are many optimization algorithms in the opti-mization toolbox of MATLABSimulink The cost functionis given by (119870
119901
119870119894
119870119889
) And the gains of the optimal PIDand optimal antiwindup PID controllers 119870
119901
119870119894
and 119870119889
can be found by using the optimization toolbox of MAT-LABSimulink To find optimal control gains the referencestep input is applied in optimization process and the responseperformance is set as follows The amplitude of reference is20mm the rising time is 04 seconds settling time is 08seconds percent overshoot is under 5 and steady-stateerror is under 01mm
In the optimization process of optimal PID and optimalantiwindup PID controllers system parameter uncertaintiesdue to the modeling error are considered Specifically plusmn10ofmodeling error is considered in terms of identified transferfunction associate with variable system parameters such aseffective bulk modulus of the working fluid and total leakagecoefficient
With respect to optimal antiwindup PID and antiwindupPID sliding mode controllers the antiwindup algorithmshown in Figure 9 is used to consider saturation in an electricmotor [2 26ndash28]
Figure 10 shows the results of a computer simulationwith optimal antiwindup PID control gains using MAT-LABSimulink optimization toolbox based on identifiedtransfer function considering model uncertainty The dottedline there shows upper bound and lower bound consideringthe plusmn10 of modeling error and straight line shows nominalsimulation result with optimal antiwindup PID control gainsAs shown in Figure 10 the simulation result with optimalgains satisfies set response performance
42 Adaptive Antiwindup SlidingModeController Consideringthe PID Sliding Surface In this study the adaptive anti-windup PID sliding mode control scheme is also designedto achieve desirable performance and robustness of EHAposition control systems Throughout the controller designprocess the effective bulk modulus and leakage coefficientsare considered as variable systemparameters In order to con-sider saturation in electric motor the antiwindup algorithmpresented in Figure 8 also applies to the adaptive antiwindupPID sliding mode control scheme
8 The Scientific World Journal
Position controller BLDC motor with controller
Motorcontroller
r i re
120596
i
Ks
Ks Km
Tm
plusmn100A
minus+
+++
+
rpmplusmn10000
minus
ka
ei
s
k2s
orKi
s
k3 or Kd
k1 or Kpe 120596p1
Jms + Bm
Figure 9 Block diagram for adopted antiwindup algorithm in controller design
06 07 08 09 1 1118
19
20
21
22Upper boundary
Lower boundary
Nominal response
0 02 04 06 08 1 12 14 16 18 20
5
10
15
20
25
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
Figure 10 Step response of the optimal antiwindup PID controlsystem in computer simulation based on identified transfer functionof EHA system
The PID sliding surface 120577 for the design of the adaptivesliding mode control system is defined as [29ndash32]
120577 = 1198961
119890 + 1198962
int 119890 119889119905 + 1198963
119890 (18)
where the tracking error of the position 119890 = 119909119889
minus 119909 119909 isthe displacement of hydraulic cylinder and 119896
1
1198962
and 1198963
arepositive design parameters
The sliding mode control law consists of equivalent androbust control term that is
120596119901
= 120596119901119890119902
+ 120596119901robust (19)
By combining (11) and (18) with consideration of the noiseterm in the jerk =
119898
+ 119899
the derivative of the slidingsurface 120577 can be written as
120577 = minus 1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
120596119901
+ 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119898
+ 119899
)
+ 1198963
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+ 1198963
119889
+ 1198961
119890 + 1198962
119890
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891
(20)
where 119891 = 1198911
+ (119862119879
119860)1198912
+ (1198810
119860119863119901
120573119890
) 1198912
is lumped uncer-tain nonlinearities of the EHA system and the subscripts 119898and 119899 denote the nominal and noisy values respectively
To determine the equivalent control term 120596119901119890119902
the noiseterm in the jerk is neglected and it is assumed that the slidingsurface 120577 is at steady-state that is 120577 = 0 and then theequivalent control law can be determined as
120596119901119890119902
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119889
(21)
Thus 120577 can be rewritten as
120577 = 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119899
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891 (22)
In the standard sliding mode control to satisfy the reach-ability condition that directs system trajectories toward asliding surface where they remain and to attenuate chatteringin the control input the derivative of the sliding surface isselected as [33 34]
120577 = minus119863120577 minus 119870 sgn (120577) (23)
where119863 and119870 are positive design parameters
The Scientific World Journal 9
To determine a robust control term120596119901robust that achieves
robustness to uncertainties such as noise terms in the jerk andunmodeled system dynamics as well as the disturbance forceit is assumed that
1198630
10038161003816100381610038161205771003816100381610038161003816 + 1198700 gt
100381610038161003816100381610038161003816100381610038161003816
1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119899
+1
1198721198810
119891)
100381610038161003816100381610038161003816100381610038161003816
+ 120578
(24)
where 1198700
= (119860119863119901
120573119890
(1198611198810
+ 119862119879
119863119901
119872120573119890
))119870 and 1198630
=
(119860119863119901
120573119890
(1198611198810
+119862119879
119863119901
119872120573119890
))119863 are positive design parametersand 120578 is sufficiently small positive parameter On the assump-tion of (24) the robust control law is determined as
120596119901robust = 119863120577 + 119870 sgn (120577) (25)
Finally the sliding mode control law is selected as
120596119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 119889
+1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119863120577 + 119870 sgn (120577)
(26)
If the total leakage coefficient 119862119879
and the effective bulkmodulus of EHA systems 120573
119890
are considered as variableparameters that is 119862
119879
= 119862119879119899
+ 119862119879119901
and 120573119890
= 120573119890119899
+ 120573119890119901
then the uncertainty 120595 is defined as
120595 = 120579119879
120593 = (1198721198810
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
) 119898
+ (
(1198602
+ 119861119862119879119901
119863119901
) 120573119890119901
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)
(27)
where 120579119879
= [(1198721198810
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)) ((1198602
+
119861119862119879119901
119863119901
)120573119890119901
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
))] and 120593 = [119909
119898
119909
] Theparameter vector 120579 is considered as an unknown parametervector and it can be estimated by using the update lawFrom (26) and estimated unknown parameter vector 120579 theestimated sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119860119863119901
120573119890119899
times 119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
+ 119863120577 + 119870 sgn (120577)
(28)
In order to obtain the update law for the unknownparameters the Lyapunov candidate is defined as
119881 =1
21205772
+1
2120574120579119879
120579 (29)
where 120579 = 120579 minus 120579 120574 is a positive parameter Also 120579 and 120579 arethe nominal and estimated parameter vectors respectivelyThe derivative of the Lyapunov candidate including slidingdynamics is expressed as
= 120577 [119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
minus1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
119901
] minus1
120574120579119879120579
(30)
Substituting the estimated angular velocity of the pump 119901
given by (28) into (30) yields
= minus1198631205772
minus 119870120577 sgn (120577) + 120579119879 (120577120593 minus 1120574
120579) (31)
From the derivative of the Lyapunov included sliding dynam-ics the update law for the unknown parameters is selected as
120579 = 120574120577120593 (32)
Therefore the derivative of the Lyapunov is given as
= minus1198631205772
minus 119870120577 sgn (120577) le 0 (33)
By applying invariant set theorem for (33) the asymptoticalstability of the EHAposition control system is guaranteed [3334]
Finally the sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times (120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890)
+ 119863120577 + 119870 sgn (120577) (34)
where 120573119890
(119905 + 119879119904
) = (119889120573119890
(119905)119889119905)119879119904
+ 120573119890
(119905) 119862119879
(119905 + 119879119904
) =
(119889119862119879
(119905)119889119905)119879119904
+ 119862119879
(119905) and 119879119904
is the sampling time
10 The Scientific World Journal
Table 3 Optimal gains of optimal PID antiwindup PID and adaptive anti-windup PID sliding mode control systems in experiments
Gain Optimal PID Optimal antiwindup PID Adaptive antiwindup PID sliding modeProportional (119870
119901
or 1198961
) 10343 16947 950Integral (119870
119894
or 1198962
) 184 10877 0001Derivative (119870
119889
or 1198963
) 47 4160 145Antiwindup (119870
119886
) mdash 0001 0001
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 11 Performances of optimal PID position control system for EHA without load disturbance (only mass load is applied)
5 Experimental Results and Discussion
This section looks to the experimental results in order tocompare the performance of a position control systemsThreekinds of controllers are compared in order to show improvedperformance of overshoot reduction and robustness to theparameter change and load disturbance of the proposedcontroller for EHA position control system
Firstly optimal PID controller is designed and imple-mented by experiments Figure 11 shows experimental resultsof the PID position controller with step references of fourdifferent amplitudes which are 10 20 30 and 40mmwithoutload disturbance that is only mass load is applied as load tothe position control system
The gains of the three-position controllers are optimallyselected by using MATLABSimulink optimization toolboxbased on identified system dynamic model of (14) In theprocess of optimal gain selection the amplitude of positionreference is set to 20mm and target performance is 04seconds of the rising time 08 seconds of settling timeunder 5 of percent overshoot and under 01mm of steady-state error In experiments the optimal gains derived fromMATLABSimulink optimization toolbox are tuned to obtainbest responses The finally tuned optimal gains of the threecontrollers are represented in Table 3
As shown in Figure 11 large overshoot is observed inposition control result for using the optimal PID positioncontroller The performance of optimal PID position control
system is represented in Table 4The performance of optimalPID controller in experiment is not satisfactory the aimedvalue In detail large overshoot is observed in experimentsThe current and angular velocity saturations of BLDC motorin position experiment result of optimal PID controller areshown in Figure 12The large overshoot in position controllercan be caused due to saturation of BLDC motor as shown inFigure 12
To reduce such a large overshoot an antiwindup algo-rithmwhich is described in Figure 9 is applied to the positioncontrol system of the EHA The performance characteristicsof an antiwindup PID position controller are depicted inFigure 13 and also the values of performance indices areshown in Table 4 As shown in Figure 13 the overshoot ofthe optimal antiwindup PID controller is more diminishedthan that of the optimal PID controller However as shown inTable 4 the antiwindupPID controller still has a performanceof relatively long settling times which do not meet the aimedperformance Moreover as the amplitude of the referenceinput increases the steady-state error is increasing as shownin Figure 13
Figure 14 shows the experimental results of optimal adap-tive antiwindup sliding mode position control system for theEHA system As shown in Figure 14 the optimal antiwindupPID sliding mode position control system has a better per-formance than the system with optimal PID and antiwindupPID controllers such that relatively small overshoot and shortsettling time are obtained by the adaptive antiwindup PID
The Scientific World Journal 11
Table 4 Comparison of the performance of optimal PID optimal antiwindup PID and adaptive antiwindup PID sliding mode controlsystems without load disturbance
Performance Reference Optimal PID Optimal antiwindup PID Adaptive antiwindup PIDsliding mode
Overshoot
10mm 389 208 1020mm 161 133 0530mm 147 119 0240mm 122 82 01
Settling time
10mm 178 sec 22 sec 06 sec20mm 056 sec 22 sec 06 sec30mm 058 sec 063 sec 07 sec40mm 069 sec 26 sec 07 sec
0 05 1 15 2 25 3minus120
minus90
minus60
minus30
0
30
60
90
120
150
Impr
esse
d cu
rren
t (A
)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(a) Saturation of impressed current
0 05 1 15 2 25 3minus6000
minus4000
minus2000
0
2000
4000
6000
8000
10000
12000
14000
Mot
or an
gula
r spe
ed (r
pm)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Saturation of angular velocity
Figure 12 Saturation of BLDCmotor for optimal PID position control system for EHAwithout load disturbance (only mass load is applied)
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 13 Performances of optimal antiwindup PID position control system for EHA without load disturbance (only mass load is applied)
12 The Scientific World Journal
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 14 Performances of optimal adaptive antiwindup PID sliding mode position control system for EHA without load disturbance (onlymass load is applied)
0 05 1 15 2 25 30
1
2
3
4
5
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 15 Pressure variations of optimal PID position control system for EHA without load disturbance (only mass load is applied)
sliding mode control system As shown in Figure 14 andTable 4 the consistent performance is realized by the optimaladaptive antiwindup PID sliding mode control system Thetime-domain quantitative performance indicators are alsosummarized in Table 4 for optimal adaptive antiwindup PIDsliding mode control system without load
On the other hand Figure 15 depicts pressure variationsof the optimal PID EHAposition control systemwithout loaddisturbance As shown in Figure 15 the range of operatingpressure of the EHA system is under 3MPa inwhich the effec-tive bulk modulus can be significantly changed according tocontained air ratio of working fluid [5 7 11ndash13] as shownin Figure 16 The range of operating pressure for antiwindup
PID and antiwindup PID sliding mode control system is alsounder 3MPa
Figure 17 depicts pressures of the EHA system when theposition control systems are operating with load disturbanceAs shown in Figure 17 the maximum operating pressures ofthe EHA system is about 10MPa when the position controlsystems are working under the condition of adding distur-bance loadThemaximumoperating pressure for antiwindupPID and antiwindup PID sliding mode control system isalso up to 10MPa Thus the effective bulk modulus can bechanged greatly according to variation of operating pressureof the EHA systems In addition total leakage coefficient alsocan be changed in response to the level of working pressure
The Scientific World Journal 13
0 5 10 15 20 25 300
400
800
1200
1600
2000
Bulk
mod
ulus
(MPa
)
Pressure (MPa)
Contained air ratio ()001
110
Figure 16 Example of the relationship between pressure and effective bulk modulus [12 13]
0 05 1 15 2 25 30123456789
101112
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 17 Pressure variations of optimal PID position control system for EHA with load disturbance
In order to investigate robustness to the lumped systemuncertainties such as varying parameters and modeling errorand load disturbance the performances of the three-positioncontrollers of EHA system are compared in experiments byapplying load disturbance The experiments are conductedwith 20mm position reference and the load disturbance isapplied by controlling the opening area of servo valve whichis installed in a meter outline of load cylinder
As shown in Figure 18 the optimal PID and optimalantiwindup PID control systems do not achieve robustnessto the parameter change and load disturbance In spite of theload disturbance and saturation of the BLDC motor in theposition control system for EHA the adaptive antiwindupPID sliding mode control system has a better performanceand robustness than the optimal PID and optimal antiwindupPID control systems such that the adaptive antiwindup PID
sliding mode control system recovers the parameter changeand external disturbance in about 09 sec with a small over-shootThe time-domain quantitative performance indicatorsare summarized in Table 5 for optimal PID antiwindup PIDand adaptive antiwindup PID sliding mode control systemswith load disturbance The list of terms are represented inTable 6
6 Conclusion
This paper discussed the application of the optimal PIDcontroller with optimal control gains using the optimizationtoolbox ofMATLABSimulink to the position control systemof EHA in order to understand the basic performancecharacteristics of the system In experiment with optimal PIDcontroller large overshoot due to saturation of electric motoris observed
14 The Scientific World Journal
0 05 1 15 2 25 30
5
10
15
20
25
30
35
Position referenceOptimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(b) Position errors
0 05 1 15 2 25 30
2
4
6
8
10
Load
forc
e (kN
)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(c) Load force
Figure 18 Performances of optimal PID antiwindup PID and adaptive antiwindup PID sliding mode control systems for EHA with loaddisturbance
Table 5 Comparison of the performance of optimal PID optimalantiwindup PID and adaptive antiwindup PID slidingmode controlsystems with load disturbance
Performance OptimalPID
Optimalantiwindup PID
Adaptive antiwindupPID sliding mode
Overshoot 45 39 12Settling time 38 sec 18 sec 08 sec
In order to achieve the desirable performance of EHAposition control system optimal antiwindup PID controller
and adaptive antiwindup PID sliding mode controller arealso applied to control the position of EHA systems Inthe process of robust control system design mathematicalmodeling was carried out based on theoretical analysisand the simple third-order nominal model was derivedThe system parameters of the simple second-order nominalmodel were identified by the signal compression method
Based on the experimental results and the time-domainquantitative performance indicators the performance of theEHA position control system can be improved and robustto the load disturbance parameter variation and system
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
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International Journal of
![Page 8: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/8.jpg)
8 The Scientific World Journal
Position controller BLDC motor with controller
Motorcontroller
r i re
120596
i
Ks
Ks Km
Tm
plusmn100A
minus+
+++
+
rpmplusmn10000
minus
ka
ei
s
k2s
orKi
s
k3 or Kd
k1 or Kpe 120596p1
Jms + Bm
Figure 9 Block diagram for adopted antiwindup algorithm in controller design
06 07 08 09 1 1118
19
20
21
22Upper boundary
Lower boundary
Nominal response
0 02 04 06 08 1 12 14 16 18 20
5
10
15
20
25
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
Figure 10 Step response of the optimal antiwindup PID controlsystem in computer simulation based on identified transfer functionof EHA system
The PID sliding surface 120577 for the design of the adaptivesliding mode control system is defined as [29ndash32]
120577 = 1198961
119890 + 1198962
int 119890 119889119905 + 1198963
119890 (18)
where the tracking error of the position 119890 = 119909119889
minus 119909 119909 isthe displacement of hydraulic cylinder and 119896
1
1198962
and 1198963
arepositive design parameters
The sliding mode control law consists of equivalent androbust control term that is
120596119901
= 120596119901119890119902
+ 120596119901robust (19)
By combining (11) and (18) with consideration of the noiseterm in the jerk =
119898
+ 119899
the derivative of the slidingsurface 120577 can be written as
120577 = minus 1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
120596119901
+ 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119898
+ 119899
)
+ 1198963
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+ 1198963
119889
+ 1198961
119890 + 1198962
119890
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891
(20)
where 119891 = 1198911
+ (119862119879
119860)1198912
+ (1198810
119860119863119901
120573119890
) 1198912
is lumped uncer-tain nonlinearities of the EHA system and the subscripts 119898and 119899 denote the nominal and noisy values respectively
To determine the equivalent control term 120596119901119890119902
the noiseterm in the jerk is neglected and it is assumed that the slidingsurface 120577 is at steady-state that is 120577 = 0 and then theequivalent control law can be determined as
120596119901119890119902
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119889
(21)
Thus 120577 can be rewritten as
120577 = 1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119899
+1198963
1198611198810
+ 119862119879
119863119901
119872120573119890
119891 (22)
In the standard sliding mode control to satisfy the reach-ability condition that directs system trajectories toward asliding surface where they remain and to attenuate chatteringin the control input the derivative of the sliding surface isselected as [33 34]
120577 = minus119863120577 minus 119870 sgn (120577) (23)
where119863 and119870 are positive design parameters
The Scientific World Journal 9
To determine a robust control term120596119901robust that achieves
robustness to uncertainties such as noise terms in the jerk andunmodeled system dynamics as well as the disturbance forceit is assumed that
1198630
10038161003816100381610038161205771003816100381610038161003816 + 1198700 gt
100381610038161003816100381610038161003816100381610038161003816
1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119899
+1
1198721198810
119891)
100381610038161003816100381610038161003816100381610038161003816
+ 120578
(24)
where 1198700
= (119860119863119901
120573119890
(1198611198810
+ 119862119879
119863119901
119872120573119890
))119870 and 1198630
=
(119860119863119901
120573119890
(1198611198810
+119862119879
119863119901
119872120573119890
))119863 are positive design parametersand 120578 is sufficiently small positive parameter On the assump-tion of (24) the robust control law is determined as
120596119901robust = 119863120577 + 119870 sgn (120577) (25)
Finally the sliding mode control law is selected as
120596119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 119889
+1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119863120577 + 119870 sgn (120577)
(26)
If the total leakage coefficient 119862119879
and the effective bulkmodulus of EHA systems 120573
119890
are considered as variableparameters that is 119862
119879
= 119862119879119899
+ 119862119879119901
and 120573119890
= 120573119890119899
+ 120573119890119901
then the uncertainty 120595 is defined as
120595 = 120579119879
120593 = (1198721198810
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
) 119898
+ (
(1198602
+ 119861119862119879119901
119863119901
) 120573119890119901
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)
(27)
where 120579119879
= [(1198721198810
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)) ((1198602
+
119861119862119879119901
119863119901
)120573119890119901
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
))] and 120593 = [119909
119898
119909
] Theparameter vector 120579 is considered as an unknown parametervector and it can be estimated by using the update lawFrom (26) and estimated unknown parameter vector 120579 theestimated sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119860119863119901
120573119890119899
times 119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
+ 119863120577 + 119870 sgn (120577)
(28)
In order to obtain the update law for the unknownparameters the Lyapunov candidate is defined as
119881 =1
21205772
+1
2120574120579119879
120579 (29)
where 120579 = 120579 minus 120579 120574 is a positive parameter Also 120579 and 120579 arethe nominal and estimated parameter vectors respectivelyThe derivative of the Lyapunov candidate including slidingdynamics is expressed as
= 120577 [119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
minus1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
119901
] minus1
120574120579119879120579
(30)
Substituting the estimated angular velocity of the pump 119901
given by (28) into (30) yields
= minus1198631205772
minus 119870120577 sgn (120577) + 120579119879 (120577120593 minus 1120574
120579) (31)
From the derivative of the Lyapunov included sliding dynam-ics the update law for the unknown parameters is selected as
120579 = 120574120577120593 (32)
Therefore the derivative of the Lyapunov is given as
= minus1198631205772
minus 119870120577 sgn (120577) le 0 (33)
By applying invariant set theorem for (33) the asymptoticalstability of the EHAposition control system is guaranteed [3334]
Finally the sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times (120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890)
+ 119863120577 + 119870 sgn (120577) (34)
where 120573119890
(119905 + 119879119904
) = (119889120573119890
(119905)119889119905)119879119904
+ 120573119890
(119905) 119862119879
(119905 + 119879119904
) =
(119889119862119879
(119905)119889119905)119879119904
+ 119862119879
(119905) and 119879119904
is the sampling time
10 The Scientific World Journal
Table 3 Optimal gains of optimal PID antiwindup PID and adaptive anti-windup PID sliding mode control systems in experiments
Gain Optimal PID Optimal antiwindup PID Adaptive antiwindup PID sliding modeProportional (119870
119901
or 1198961
) 10343 16947 950Integral (119870
119894
or 1198962
) 184 10877 0001Derivative (119870
119889
or 1198963
) 47 4160 145Antiwindup (119870
119886
) mdash 0001 0001
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 11 Performances of optimal PID position control system for EHA without load disturbance (only mass load is applied)
5 Experimental Results and Discussion
This section looks to the experimental results in order tocompare the performance of a position control systemsThreekinds of controllers are compared in order to show improvedperformance of overshoot reduction and robustness to theparameter change and load disturbance of the proposedcontroller for EHA position control system
Firstly optimal PID controller is designed and imple-mented by experiments Figure 11 shows experimental resultsof the PID position controller with step references of fourdifferent amplitudes which are 10 20 30 and 40mmwithoutload disturbance that is only mass load is applied as load tothe position control system
The gains of the three-position controllers are optimallyselected by using MATLABSimulink optimization toolboxbased on identified system dynamic model of (14) In theprocess of optimal gain selection the amplitude of positionreference is set to 20mm and target performance is 04seconds of the rising time 08 seconds of settling timeunder 5 of percent overshoot and under 01mm of steady-state error In experiments the optimal gains derived fromMATLABSimulink optimization toolbox are tuned to obtainbest responses The finally tuned optimal gains of the threecontrollers are represented in Table 3
As shown in Figure 11 large overshoot is observed inposition control result for using the optimal PID positioncontroller The performance of optimal PID position control
system is represented in Table 4The performance of optimalPID controller in experiment is not satisfactory the aimedvalue In detail large overshoot is observed in experimentsThe current and angular velocity saturations of BLDC motorin position experiment result of optimal PID controller areshown in Figure 12The large overshoot in position controllercan be caused due to saturation of BLDC motor as shown inFigure 12
To reduce such a large overshoot an antiwindup algo-rithmwhich is described in Figure 9 is applied to the positioncontrol system of the EHA The performance characteristicsof an antiwindup PID position controller are depicted inFigure 13 and also the values of performance indices areshown in Table 4 As shown in Figure 13 the overshoot ofthe optimal antiwindup PID controller is more diminishedthan that of the optimal PID controller However as shown inTable 4 the antiwindupPID controller still has a performanceof relatively long settling times which do not meet the aimedperformance Moreover as the amplitude of the referenceinput increases the steady-state error is increasing as shownin Figure 13
Figure 14 shows the experimental results of optimal adap-tive antiwindup sliding mode position control system for theEHA system As shown in Figure 14 the optimal antiwindupPID sliding mode position control system has a better per-formance than the system with optimal PID and antiwindupPID controllers such that relatively small overshoot and shortsettling time are obtained by the adaptive antiwindup PID
The Scientific World Journal 11
Table 4 Comparison of the performance of optimal PID optimal antiwindup PID and adaptive antiwindup PID sliding mode controlsystems without load disturbance
Performance Reference Optimal PID Optimal antiwindup PID Adaptive antiwindup PIDsliding mode
Overshoot
10mm 389 208 1020mm 161 133 0530mm 147 119 0240mm 122 82 01
Settling time
10mm 178 sec 22 sec 06 sec20mm 056 sec 22 sec 06 sec30mm 058 sec 063 sec 07 sec40mm 069 sec 26 sec 07 sec
0 05 1 15 2 25 3minus120
minus90
minus60
minus30
0
30
60
90
120
150
Impr
esse
d cu
rren
t (A
)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(a) Saturation of impressed current
0 05 1 15 2 25 3minus6000
minus4000
minus2000
0
2000
4000
6000
8000
10000
12000
14000
Mot
or an
gula
r spe
ed (r
pm)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Saturation of angular velocity
Figure 12 Saturation of BLDCmotor for optimal PID position control system for EHAwithout load disturbance (only mass load is applied)
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 13 Performances of optimal antiwindup PID position control system for EHA without load disturbance (only mass load is applied)
12 The Scientific World Journal
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 14 Performances of optimal adaptive antiwindup PID sliding mode position control system for EHA without load disturbance (onlymass load is applied)
0 05 1 15 2 25 30
1
2
3
4
5
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 15 Pressure variations of optimal PID position control system for EHA without load disturbance (only mass load is applied)
sliding mode control system As shown in Figure 14 andTable 4 the consistent performance is realized by the optimaladaptive antiwindup PID sliding mode control system Thetime-domain quantitative performance indicators are alsosummarized in Table 4 for optimal adaptive antiwindup PIDsliding mode control system without load
On the other hand Figure 15 depicts pressure variationsof the optimal PID EHAposition control systemwithout loaddisturbance As shown in Figure 15 the range of operatingpressure of the EHA system is under 3MPa inwhich the effec-tive bulk modulus can be significantly changed according tocontained air ratio of working fluid [5 7 11ndash13] as shownin Figure 16 The range of operating pressure for antiwindup
PID and antiwindup PID sliding mode control system is alsounder 3MPa
Figure 17 depicts pressures of the EHA system when theposition control systems are operating with load disturbanceAs shown in Figure 17 the maximum operating pressures ofthe EHA system is about 10MPa when the position controlsystems are working under the condition of adding distur-bance loadThemaximumoperating pressure for antiwindupPID and antiwindup PID sliding mode control system isalso up to 10MPa Thus the effective bulk modulus can bechanged greatly according to variation of operating pressureof the EHA systems In addition total leakage coefficient alsocan be changed in response to the level of working pressure
The Scientific World Journal 13
0 5 10 15 20 25 300
400
800
1200
1600
2000
Bulk
mod
ulus
(MPa
)
Pressure (MPa)
Contained air ratio ()001
110
Figure 16 Example of the relationship between pressure and effective bulk modulus [12 13]
0 05 1 15 2 25 30123456789
101112
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 17 Pressure variations of optimal PID position control system for EHA with load disturbance
In order to investigate robustness to the lumped systemuncertainties such as varying parameters and modeling errorand load disturbance the performances of the three-positioncontrollers of EHA system are compared in experiments byapplying load disturbance The experiments are conductedwith 20mm position reference and the load disturbance isapplied by controlling the opening area of servo valve whichis installed in a meter outline of load cylinder
As shown in Figure 18 the optimal PID and optimalantiwindup PID control systems do not achieve robustnessto the parameter change and load disturbance In spite of theload disturbance and saturation of the BLDC motor in theposition control system for EHA the adaptive antiwindupPID sliding mode control system has a better performanceand robustness than the optimal PID and optimal antiwindupPID control systems such that the adaptive antiwindup PID
sliding mode control system recovers the parameter changeand external disturbance in about 09 sec with a small over-shootThe time-domain quantitative performance indicatorsare summarized in Table 5 for optimal PID antiwindup PIDand adaptive antiwindup PID sliding mode control systemswith load disturbance The list of terms are represented inTable 6
6 Conclusion
This paper discussed the application of the optimal PIDcontroller with optimal control gains using the optimizationtoolbox ofMATLABSimulink to the position control systemof EHA in order to understand the basic performancecharacteristics of the system In experiment with optimal PIDcontroller large overshoot due to saturation of electric motoris observed
14 The Scientific World Journal
0 05 1 15 2 25 30
5
10
15
20
25
30
35
Position referenceOptimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(b) Position errors
0 05 1 15 2 25 30
2
4
6
8
10
Load
forc
e (kN
)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(c) Load force
Figure 18 Performances of optimal PID antiwindup PID and adaptive antiwindup PID sliding mode control systems for EHA with loaddisturbance
Table 5 Comparison of the performance of optimal PID optimalantiwindup PID and adaptive antiwindup PID slidingmode controlsystems with load disturbance
Performance OptimalPID
Optimalantiwindup PID
Adaptive antiwindupPID sliding mode
Overshoot 45 39 12Settling time 38 sec 18 sec 08 sec
In order to achieve the desirable performance of EHAposition control system optimal antiwindup PID controller
and adaptive antiwindup PID sliding mode controller arealso applied to control the position of EHA systems Inthe process of robust control system design mathematicalmodeling was carried out based on theoretical analysisand the simple third-order nominal model was derivedThe system parameters of the simple second-order nominalmodel were identified by the signal compression method
Based on the experimental results and the time-domainquantitative performance indicators the performance of theEHA position control system can be improved and robustto the load disturbance parameter variation and system
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
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DistributedSensor Networks
International Journal of
![Page 9: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/9.jpg)
The Scientific World Journal 9
To determine a robust control term120596119901robust that achieves
robustness to uncertainties such as noise terms in the jerk andunmodeled system dynamics as well as the disturbance forceit is assumed that
1198630
10038161003816100381610038161205771003816100381610038161003816 + 1198700 gt
100381610038161003816100381610038161003816100381610038161003816
1198963
1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
(119899
+1
1198721198810
119891)
100381610038161003816100381610038161003816100381610038161003816
+ 120578
(24)
where 1198700
= (119860119863119901
120573119890
(1198611198810
+ 119862119879
119863119901
119872120573119890
))119870 and 1198630
=
(119860119863119901
120573119890
(1198611198810
+119862119879
119863119901
119872120573119890
))119863 are positive design parametersand 120578 is sufficiently small positive parameter On the assump-tion of (24) the robust control law is determined as
120596119901robust = 119863120577 + 119870 sgn (120577) (25)
Finally the sliding mode control law is selected as
120596119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times 119889
+1198721198810
1198611198810
+ 119862119879
119863119901
119872120573119890
119898
+
(1198602
+ 119861119862119879
119863119901
) 120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
+1198961
1198963
119890 +1198962
1198963
119890 + 119863120577 + 119870 sgn (120577)
(26)
If the total leakage coefficient 119862119879
and the effective bulkmodulus of EHA systems 120573
119890
are considered as variableparameters that is 119862
119879
= 119862119879119899
+ 119862119879119901
and 120573119890
= 120573119890119899
+ 120573119890119901
then the uncertainty 120595 is defined as
120595 = 120579119879
120593 = (1198721198810
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
) 119898
+ (
(1198602
+ 119861119862119879119901
119863119901
) 120573119890119901
1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)
(27)
where 120579119879
= [(1198721198810
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
)) ((1198602
+
119861119862119879119901
119863119901
)120573119890119901
(1198611198810
+ 119862119879119901
119863119901
119872120573119890119901
))] and 120593 = [119909
119898
119909
] Theparameter vector 120579 is considered as an unknown parametervector and it can be estimated by using the update lawFrom (26) and estimated unknown parameter vector 120579 theestimated sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119860119863119901
120573119890119899
times 119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
+ 119863120577 + 119870 sgn (120577)
(28)
In order to obtain the update law for the unknownparameters the Lyapunov candidate is defined as
119881 =1
21205772
+1
2120574120579119879
120579 (29)
where 120579 = 120579 minus 120579 120574 is a positive parameter Also 120579 and 120579 arethe nominal and estimated parameter vectors respectivelyThe derivative of the Lyapunov candidate including slidingdynamics is expressed as
= 120577 [119889
+ 120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890
minus1198963
119860119863119901
120573119890
1198611198810
+ 119862119879
119863119901
119872120573119890
119901
] minus1
120574120579119879120579
(30)
Substituting the estimated angular velocity of the pump 119901
given by (28) into (30) yields
= minus1198631205772
minus 119870120577 sgn (120577) + 120579119879 (120577120593 minus 1120574
120579) (31)
From the derivative of the Lyapunov included sliding dynam-ics the update law for the unknown parameters is selected as
120579 = 120574120577120593 (32)
Therefore the derivative of the Lyapunov is given as
= minus1198631205772
minus 119870120577 sgn (120577) le 0 (33)
By applying invariant set theorem for (33) the asymptoticalstability of the EHAposition control system is guaranteed [3334]
Finally the sliding mode control law can be selected as
119901
=
1198611198810
+ 119862119879
119863119901
119872120573119890
119860119863119901
120573119890
times (120579119879
120593 +1198721198810
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
119898
+
(1198602
+ 119861119862119879119899
119863119901
) 120573119890119899
1198611198810
+ 119862119879119899
119863119901
119872120573119890119899
+1198961
1198963
119890 +1198962
1198963
119890)
+ 119863120577 + 119870 sgn (120577) (34)
where 120573119890
(119905 + 119879119904
) = (119889120573119890
(119905)119889119905)119879119904
+ 120573119890
(119905) 119862119879
(119905 + 119879119904
) =
(119889119862119879
(119905)119889119905)119879119904
+ 119862119879
(119905) and 119879119904
is the sampling time
10 The Scientific World Journal
Table 3 Optimal gains of optimal PID antiwindup PID and adaptive anti-windup PID sliding mode control systems in experiments
Gain Optimal PID Optimal antiwindup PID Adaptive antiwindup PID sliding modeProportional (119870
119901
or 1198961
) 10343 16947 950Integral (119870
119894
or 1198962
) 184 10877 0001Derivative (119870
119889
or 1198963
) 47 4160 145Antiwindup (119870
119886
) mdash 0001 0001
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 11 Performances of optimal PID position control system for EHA without load disturbance (only mass load is applied)
5 Experimental Results and Discussion
This section looks to the experimental results in order tocompare the performance of a position control systemsThreekinds of controllers are compared in order to show improvedperformance of overshoot reduction and robustness to theparameter change and load disturbance of the proposedcontroller for EHA position control system
Firstly optimal PID controller is designed and imple-mented by experiments Figure 11 shows experimental resultsof the PID position controller with step references of fourdifferent amplitudes which are 10 20 30 and 40mmwithoutload disturbance that is only mass load is applied as load tothe position control system
The gains of the three-position controllers are optimallyselected by using MATLABSimulink optimization toolboxbased on identified system dynamic model of (14) In theprocess of optimal gain selection the amplitude of positionreference is set to 20mm and target performance is 04seconds of the rising time 08 seconds of settling timeunder 5 of percent overshoot and under 01mm of steady-state error In experiments the optimal gains derived fromMATLABSimulink optimization toolbox are tuned to obtainbest responses The finally tuned optimal gains of the threecontrollers are represented in Table 3
As shown in Figure 11 large overshoot is observed inposition control result for using the optimal PID positioncontroller The performance of optimal PID position control
system is represented in Table 4The performance of optimalPID controller in experiment is not satisfactory the aimedvalue In detail large overshoot is observed in experimentsThe current and angular velocity saturations of BLDC motorin position experiment result of optimal PID controller areshown in Figure 12The large overshoot in position controllercan be caused due to saturation of BLDC motor as shown inFigure 12
To reduce such a large overshoot an antiwindup algo-rithmwhich is described in Figure 9 is applied to the positioncontrol system of the EHA The performance characteristicsof an antiwindup PID position controller are depicted inFigure 13 and also the values of performance indices areshown in Table 4 As shown in Figure 13 the overshoot ofthe optimal antiwindup PID controller is more diminishedthan that of the optimal PID controller However as shown inTable 4 the antiwindupPID controller still has a performanceof relatively long settling times which do not meet the aimedperformance Moreover as the amplitude of the referenceinput increases the steady-state error is increasing as shownin Figure 13
Figure 14 shows the experimental results of optimal adap-tive antiwindup sliding mode position control system for theEHA system As shown in Figure 14 the optimal antiwindupPID sliding mode position control system has a better per-formance than the system with optimal PID and antiwindupPID controllers such that relatively small overshoot and shortsettling time are obtained by the adaptive antiwindup PID
The Scientific World Journal 11
Table 4 Comparison of the performance of optimal PID optimal antiwindup PID and adaptive antiwindup PID sliding mode controlsystems without load disturbance
Performance Reference Optimal PID Optimal antiwindup PID Adaptive antiwindup PIDsliding mode
Overshoot
10mm 389 208 1020mm 161 133 0530mm 147 119 0240mm 122 82 01
Settling time
10mm 178 sec 22 sec 06 sec20mm 056 sec 22 sec 06 sec30mm 058 sec 063 sec 07 sec40mm 069 sec 26 sec 07 sec
0 05 1 15 2 25 3minus120
minus90
minus60
minus30
0
30
60
90
120
150
Impr
esse
d cu
rren
t (A
)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(a) Saturation of impressed current
0 05 1 15 2 25 3minus6000
minus4000
minus2000
0
2000
4000
6000
8000
10000
12000
14000
Mot
or an
gula
r spe
ed (r
pm)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Saturation of angular velocity
Figure 12 Saturation of BLDCmotor for optimal PID position control system for EHAwithout load disturbance (only mass load is applied)
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 13 Performances of optimal antiwindup PID position control system for EHA without load disturbance (only mass load is applied)
12 The Scientific World Journal
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 14 Performances of optimal adaptive antiwindup PID sliding mode position control system for EHA without load disturbance (onlymass load is applied)
0 05 1 15 2 25 30
1
2
3
4
5
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 15 Pressure variations of optimal PID position control system for EHA without load disturbance (only mass load is applied)
sliding mode control system As shown in Figure 14 andTable 4 the consistent performance is realized by the optimaladaptive antiwindup PID sliding mode control system Thetime-domain quantitative performance indicators are alsosummarized in Table 4 for optimal adaptive antiwindup PIDsliding mode control system without load
On the other hand Figure 15 depicts pressure variationsof the optimal PID EHAposition control systemwithout loaddisturbance As shown in Figure 15 the range of operatingpressure of the EHA system is under 3MPa inwhich the effec-tive bulk modulus can be significantly changed according tocontained air ratio of working fluid [5 7 11ndash13] as shownin Figure 16 The range of operating pressure for antiwindup
PID and antiwindup PID sliding mode control system is alsounder 3MPa
Figure 17 depicts pressures of the EHA system when theposition control systems are operating with load disturbanceAs shown in Figure 17 the maximum operating pressures ofthe EHA system is about 10MPa when the position controlsystems are working under the condition of adding distur-bance loadThemaximumoperating pressure for antiwindupPID and antiwindup PID sliding mode control system isalso up to 10MPa Thus the effective bulk modulus can bechanged greatly according to variation of operating pressureof the EHA systems In addition total leakage coefficient alsocan be changed in response to the level of working pressure
The Scientific World Journal 13
0 5 10 15 20 25 300
400
800
1200
1600
2000
Bulk
mod
ulus
(MPa
)
Pressure (MPa)
Contained air ratio ()001
110
Figure 16 Example of the relationship between pressure and effective bulk modulus [12 13]
0 05 1 15 2 25 30123456789
101112
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 17 Pressure variations of optimal PID position control system for EHA with load disturbance
In order to investigate robustness to the lumped systemuncertainties such as varying parameters and modeling errorand load disturbance the performances of the three-positioncontrollers of EHA system are compared in experiments byapplying load disturbance The experiments are conductedwith 20mm position reference and the load disturbance isapplied by controlling the opening area of servo valve whichis installed in a meter outline of load cylinder
As shown in Figure 18 the optimal PID and optimalantiwindup PID control systems do not achieve robustnessto the parameter change and load disturbance In spite of theload disturbance and saturation of the BLDC motor in theposition control system for EHA the adaptive antiwindupPID sliding mode control system has a better performanceand robustness than the optimal PID and optimal antiwindupPID control systems such that the adaptive antiwindup PID
sliding mode control system recovers the parameter changeand external disturbance in about 09 sec with a small over-shootThe time-domain quantitative performance indicatorsare summarized in Table 5 for optimal PID antiwindup PIDand adaptive antiwindup PID sliding mode control systemswith load disturbance The list of terms are represented inTable 6
6 Conclusion
This paper discussed the application of the optimal PIDcontroller with optimal control gains using the optimizationtoolbox ofMATLABSimulink to the position control systemof EHA in order to understand the basic performancecharacteristics of the system In experiment with optimal PIDcontroller large overshoot due to saturation of electric motoris observed
14 The Scientific World Journal
0 05 1 15 2 25 30
5
10
15
20
25
30
35
Position referenceOptimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(b) Position errors
0 05 1 15 2 25 30
2
4
6
8
10
Load
forc
e (kN
)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(c) Load force
Figure 18 Performances of optimal PID antiwindup PID and adaptive antiwindup PID sliding mode control systems for EHA with loaddisturbance
Table 5 Comparison of the performance of optimal PID optimalantiwindup PID and adaptive antiwindup PID slidingmode controlsystems with load disturbance
Performance OptimalPID
Optimalantiwindup PID
Adaptive antiwindupPID sliding mode
Overshoot 45 39 12Settling time 38 sec 18 sec 08 sec
In order to achieve the desirable performance of EHAposition control system optimal antiwindup PID controller
and adaptive antiwindup PID sliding mode controller arealso applied to control the position of EHA systems Inthe process of robust control system design mathematicalmodeling was carried out based on theoretical analysisand the simple third-order nominal model was derivedThe system parameters of the simple second-order nominalmodel were identified by the signal compression method
Based on the experimental results and the time-domainquantitative performance indicators the performance of theEHA position control system can be improved and robustto the load disturbance parameter variation and system
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
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DistributedSensor Networks
International Journal of
![Page 10: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/10.jpg)
10 The Scientific World Journal
Table 3 Optimal gains of optimal PID antiwindup PID and adaptive anti-windup PID sliding mode control systems in experiments
Gain Optimal PID Optimal antiwindup PID Adaptive antiwindup PID sliding modeProportional (119870
119901
or 1198961
) 10343 16947 950Integral (119870
119894
or 1198962
) 184 10877 0001Derivative (119870
119889
or 1198963
) 47 4160 145Antiwindup (119870
119886
) mdash 0001 0001
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 11 Performances of optimal PID position control system for EHA without load disturbance (only mass load is applied)
5 Experimental Results and Discussion
This section looks to the experimental results in order tocompare the performance of a position control systemsThreekinds of controllers are compared in order to show improvedperformance of overshoot reduction and robustness to theparameter change and load disturbance of the proposedcontroller for EHA position control system
Firstly optimal PID controller is designed and imple-mented by experiments Figure 11 shows experimental resultsof the PID position controller with step references of fourdifferent amplitudes which are 10 20 30 and 40mmwithoutload disturbance that is only mass load is applied as load tothe position control system
The gains of the three-position controllers are optimallyselected by using MATLABSimulink optimization toolboxbased on identified system dynamic model of (14) In theprocess of optimal gain selection the amplitude of positionreference is set to 20mm and target performance is 04seconds of the rising time 08 seconds of settling timeunder 5 of percent overshoot and under 01mm of steady-state error In experiments the optimal gains derived fromMATLABSimulink optimization toolbox are tuned to obtainbest responses The finally tuned optimal gains of the threecontrollers are represented in Table 3
As shown in Figure 11 large overshoot is observed inposition control result for using the optimal PID positioncontroller The performance of optimal PID position control
system is represented in Table 4The performance of optimalPID controller in experiment is not satisfactory the aimedvalue In detail large overshoot is observed in experimentsThe current and angular velocity saturations of BLDC motorin position experiment result of optimal PID controller areshown in Figure 12The large overshoot in position controllercan be caused due to saturation of BLDC motor as shown inFigure 12
To reduce such a large overshoot an antiwindup algo-rithmwhich is described in Figure 9 is applied to the positioncontrol system of the EHA The performance characteristicsof an antiwindup PID position controller are depicted inFigure 13 and also the values of performance indices areshown in Table 4 As shown in Figure 13 the overshoot ofthe optimal antiwindup PID controller is more diminishedthan that of the optimal PID controller However as shown inTable 4 the antiwindupPID controller still has a performanceof relatively long settling times which do not meet the aimedperformance Moreover as the amplitude of the referenceinput increases the steady-state error is increasing as shownin Figure 13
Figure 14 shows the experimental results of optimal adap-tive antiwindup sliding mode position control system for theEHA system As shown in Figure 14 the optimal antiwindupPID sliding mode position control system has a better per-formance than the system with optimal PID and antiwindupPID controllers such that relatively small overshoot and shortsettling time are obtained by the adaptive antiwindup PID
The Scientific World Journal 11
Table 4 Comparison of the performance of optimal PID optimal antiwindup PID and adaptive antiwindup PID sliding mode controlsystems without load disturbance
Performance Reference Optimal PID Optimal antiwindup PID Adaptive antiwindup PIDsliding mode
Overshoot
10mm 389 208 1020mm 161 133 0530mm 147 119 0240mm 122 82 01
Settling time
10mm 178 sec 22 sec 06 sec20mm 056 sec 22 sec 06 sec30mm 058 sec 063 sec 07 sec40mm 069 sec 26 sec 07 sec
0 05 1 15 2 25 3minus120
minus90
minus60
minus30
0
30
60
90
120
150
Impr
esse
d cu
rren
t (A
)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(a) Saturation of impressed current
0 05 1 15 2 25 3minus6000
minus4000
minus2000
0
2000
4000
6000
8000
10000
12000
14000
Mot
or an
gula
r spe
ed (r
pm)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Saturation of angular velocity
Figure 12 Saturation of BLDCmotor for optimal PID position control system for EHAwithout load disturbance (only mass load is applied)
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 13 Performances of optimal antiwindup PID position control system for EHA without load disturbance (only mass load is applied)
12 The Scientific World Journal
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 14 Performances of optimal adaptive antiwindup PID sliding mode position control system for EHA without load disturbance (onlymass load is applied)
0 05 1 15 2 25 30
1
2
3
4
5
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 15 Pressure variations of optimal PID position control system for EHA without load disturbance (only mass load is applied)
sliding mode control system As shown in Figure 14 andTable 4 the consistent performance is realized by the optimaladaptive antiwindup PID sliding mode control system Thetime-domain quantitative performance indicators are alsosummarized in Table 4 for optimal adaptive antiwindup PIDsliding mode control system without load
On the other hand Figure 15 depicts pressure variationsof the optimal PID EHAposition control systemwithout loaddisturbance As shown in Figure 15 the range of operatingpressure of the EHA system is under 3MPa inwhich the effec-tive bulk modulus can be significantly changed according tocontained air ratio of working fluid [5 7 11ndash13] as shownin Figure 16 The range of operating pressure for antiwindup
PID and antiwindup PID sliding mode control system is alsounder 3MPa
Figure 17 depicts pressures of the EHA system when theposition control systems are operating with load disturbanceAs shown in Figure 17 the maximum operating pressures ofthe EHA system is about 10MPa when the position controlsystems are working under the condition of adding distur-bance loadThemaximumoperating pressure for antiwindupPID and antiwindup PID sliding mode control system isalso up to 10MPa Thus the effective bulk modulus can bechanged greatly according to variation of operating pressureof the EHA systems In addition total leakage coefficient alsocan be changed in response to the level of working pressure
The Scientific World Journal 13
0 5 10 15 20 25 300
400
800
1200
1600
2000
Bulk
mod
ulus
(MPa
)
Pressure (MPa)
Contained air ratio ()001
110
Figure 16 Example of the relationship between pressure and effective bulk modulus [12 13]
0 05 1 15 2 25 30123456789
101112
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 17 Pressure variations of optimal PID position control system for EHA with load disturbance
In order to investigate robustness to the lumped systemuncertainties such as varying parameters and modeling errorand load disturbance the performances of the three-positioncontrollers of EHA system are compared in experiments byapplying load disturbance The experiments are conductedwith 20mm position reference and the load disturbance isapplied by controlling the opening area of servo valve whichis installed in a meter outline of load cylinder
As shown in Figure 18 the optimal PID and optimalantiwindup PID control systems do not achieve robustnessto the parameter change and load disturbance In spite of theload disturbance and saturation of the BLDC motor in theposition control system for EHA the adaptive antiwindupPID sliding mode control system has a better performanceand robustness than the optimal PID and optimal antiwindupPID control systems such that the adaptive antiwindup PID
sliding mode control system recovers the parameter changeand external disturbance in about 09 sec with a small over-shootThe time-domain quantitative performance indicatorsare summarized in Table 5 for optimal PID antiwindup PIDand adaptive antiwindup PID sliding mode control systemswith load disturbance The list of terms are represented inTable 6
6 Conclusion
This paper discussed the application of the optimal PIDcontroller with optimal control gains using the optimizationtoolbox ofMATLABSimulink to the position control systemof EHA in order to understand the basic performancecharacteristics of the system In experiment with optimal PIDcontroller large overshoot due to saturation of electric motoris observed
14 The Scientific World Journal
0 05 1 15 2 25 30
5
10
15
20
25
30
35
Position referenceOptimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(b) Position errors
0 05 1 15 2 25 30
2
4
6
8
10
Load
forc
e (kN
)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(c) Load force
Figure 18 Performances of optimal PID antiwindup PID and adaptive antiwindup PID sliding mode control systems for EHA with loaddisturbance
Table 5 Comparison of the performance of optimal PID optimalantiwindup PID and adaptive antiwindup PID slidingmode controlsystems with load disturbance
Performance OptimalPID
Optimalantiwindup PID
Adaptive antiwindupPID sliding mode
Overshoot 45 39 12Settling time 38 sec 18 sec 08 sec
In order to achieve the desirable performance of EHAposition control system optimal antiwindup PID controller
and adaptive antiwindup PID sliding mode controller arealso applied to control the position of EHA systems Inthe process of robust control system design mathematicalmodeling was carried out based on theoretical analysisand the simple third-order nominal model was derivedThe system parameters of the simple second-order nominalmodel were identified by the signal compression method
Based on the experimental results and the time-domainquantitative performance indicators the performance of theEHA position control system can be improved and robustto the load disturbance parameter variation and system
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
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International Journal of
![Page 11: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/11.jpg)
The Scientific World Journal 11
Table 4 Comparison of the performance of optimal PID optimal antiwindup PID and adaptive antiwindup PID sliding mode controlsystems without load disturbance
Performance Reference Optimal PID Optimal antiwindup PID Adaptive antiwindup PIDsliding mode
Overshoot
10mm 389 208 1020mm 161 133 0530mm 147 119 0240mm 122 82 01
Settling time
10mm 178 sec 22 sec 06 sec20mm 056 sec 22 sec 06 sec30mm 058 sec 063 sec 07 sec40mm 069 sec 26 sec 07 sec
0 05 1 15 2 25 3minus120
minus90
minus60
minus30
0
30
60
90
120
150
Impr
esse
d cu
rren
t (A
)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(a) Saturation of impressed current
0 05 1 15 2 25 3minus6000
minus4000
minus2000
0
2000
4000
6000
8000
10000
12000
14000
Mot
or an
gula
r spe
ed (r
pm)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Saturation of angular velocity
Figure 12 Saturation of BLDCmotor for optimal PID position control system for EHAwithout load disturbance (only mass load is applied)
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 13 Performances of optimal antiwindup PID position control system for EHA without load disturbance (only mass load is applied)
12 The Scientific World Journal
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 14 Performances of optimal adaptive antiwindup PID sliding mode position control system for EHA without load disturbance (onlymass load is applied)
0 05 1 15 2 25 30
1
2
3
4
5
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 15 Pressure variations of optimal PID position control system for EHA without load disturbance (only mass load is applied)
sliding mode control system As shown in Figure 14 andTable 4 the consistent performance is realized by the optimaladaptive antiwindup PID sliding mode control system Thetime-domain quantitative performance indicators are alsosummarized in Table 4 for optimal adaptive antiwindup PIDsliding mode control system without load
On the other hand Figure 15 depicts pressure variationsof the optimal PID EHAposition control systemwithout loaddisturbance As shown in Figure 15 the range of operatingpressure of the EHA system is under 3MPa inwhich the effec-tive bulk modulus can be significantly changed according tocontained air ratio of working fluid [5 7 11ndash13] as shownin Figure 16 The range of operating pressure for antiwindup
PID and antiwindup PID sliding mode control system is alsounder 3MPa
Figure 17 depicts pressures of the EHA system when theposition control systems are operating with load disturbanceAs shown in Figure 17 the maximum operating pressures ofthe EHA system is about 10MPa when the position controlsystems are working under the condition of adding distur-bance loadThemaximumoperating pressure for antiwindupPID and antiwindup PID sliding mode control system isalso up to 10MPa Thus the effective bulk modulus can bechanged greatly according to variation of operating pressureof the EHA systems In addition total leakage coefficient alsocan be changed in response to the level of working pressure
The Scientific World Journal 13
0 5 10 15 20 25 300
400
800
1200
1600
2000
Bulk
mod
ulus
(MPa
)
Pressure (MPa)
Contained air ratio ()001
110
Figure 16 Example of the relationship between pressure and effective bulk modulus [12 13]
0 05 1 15 2 25 30123456789
101112
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 17 Pressure variations of optimal PID position control system for EHA with load disturbance
In order to investigate robustness to the lumped systemuncertainties such as varying parameters and modeling errorand load disturbance the performances of the three-positioncontrollers of EHA system are compared in experiments byapplying load disturbance The experiments are conductedwith 20mm position reference and the load disturbance isapplied by controlling the opening area of servo valve whichis installed in a meter outline of load cylinder
As shown in Figure 18 the optimal PID and optimalantiwindup PID control systems do not achieve robustnessto the parameter change and load disturbance In spite of theload disturbance and saturation of the BLDC motor in theposition control system for EHA the adaptive antiwindupPID sliding mode control system has a better performanceand robustness than the optimal PID and optimal antiwindupPID control systems such that the adaptive antiwindup PID
sliding mode control system recovers the parameter changeand external disturbance in about 09 sec with a small over-shootThe time-domain quantitative performance indicatorsare summarized in Table 5 for optimal PID antiwindup PIDand adaptive antiwindup PID sliding mode control systemswith load disturbance The list of terms are represented inTable 6
6 Conclusion
This paper discussed the application of the optimal PIDcontroller with optimal control gains using the optimizationtoolbox ofMATLABSimulink to the position control systemof EHA in order to understand the basic performancecharacteristics of the system In experiment with optimal PIDcontroller large overshoot due to saturation of electric motoris observed
14 The Scientific World Journal
0 05 1 15 2 25 30
5
10
15
20
25
30
35
Position referenceOptimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(b) Position errors
0 05 1 15 2 25 30
2
4
6
8
10
Load
forc
e (kN
)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(c) Load force
Figure 18 Performances of optimal PID antiwindup PID and adaptive antiwindup PID sliding mode control systems for EHA with loaddisturbance
Table 5 Comparison of the performance of optimal PID optimalantiwindup PID and adaptive antiwindup PID slidingmode controlsystems with load disturbance
Performance OptimalPID
Optimalantiwindup PID
Adaptive antiwindupPID sliding mode
Overshoot 45 39 12Settling time 38 sec 18 sec 08 sec
In order to achieve the desirable performance of EHAposition control system optimal antiwindup PID controller
and adaptive antiwindup PID sliding mode controller arealso applied to control the position of EHA systems Inthe process of robust control system design mathematicalmodeling was carried out based on theoretical analysisand the simple third-order nominal model was derivedThe system parameters of the simple second-order nominalmodel were identified by the signal compression method
Based on the experimental results and the time-domainquantitative performance indicators the performance of theEHA position control system can be improved and robustto the load disturbance parameter variation and system
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
![Page 12: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/12.jpg)
12 The Scientific World Journal
0 05 1 15 2 25 305
10152025303540455055
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
Position referencePosition
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Reference 10 mmReference 20 mm
Reference 30 mmReference 40 mm
(b) Position errors
Figure 14 Performances of optimal adaptive antiwindup PID sliding mode position control system for EHA without load disturbance (onlymass load is applied)
0 05 1 15 2 25 30
1
2
3
4
5
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 15 Pressure variations of optimal PID position control system for EHA without load disturbance (only mass load is applied)
sliding mode control system As shown in Figure 14 andTable 4 the consistent performance is realized by the optimaladaptive antiwindup PID sliding mode control system Thetime-domain quantitative performance indicators are alsosummarized in Table 4 for optimal adaptive antiwindup PIDsliding mode control system without load
On the other hand Figure 15 depicts pressure variationsof the optimal PID EHAposition control systemwithout loaddisturbance As shown in Figure 15 the range of operatingpressure of the EHA system is under 3MPa inwhich the effec-tive bulk modulus can be significantly changed according tocontained air ratio of working fluid [5 7 11ndash13] as shownin Figure 16 The range of operating pressure for antiwindup
PID and antiwindup PID sliding mode control system is alsounder 3MPa
Figure 17 depicts pressures of the EHA system when theposition control systems are operating with load disturbanceAs shown in Figure 17 the maximum operating pressures ofthe EHA system is about 10MPa when the position controlsystems are working under the condition of adding distur-bance loadThemaximumoperating pressure for antiwindupPID and antiwindup PID sliding mode control system isalso up to 10MPa Thus the effective bulk modulus can bechanged greatly according to variation of operating pressureof the EHA systems In addition total leakage coefficient alsocan be changed in response to the level of working pressure
The Scientific World Journal 13
0 5 10 15 20 25 300
400
800
1200
1600
2000
Bulk
mod
ulus
(MPa
)
Pressure (MPa)
Contained air ratio ()001
110
Figure 16 Example of the relationship between pressure and effective bulk modulus [12 13]
0 05 1 15 2 25 30123456789
101112
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 17 Pressure variations of optimal PID position control system for EHA with load disturbance
In order to investigate robustness to the lumped systemuncertainties such as varying parameters and modeling errorand load disturbance the performances of the three-positioncontrollers of EHA system are compared in experiments byapplying load disturbance The experiments are conductedwith 20mm position reference and the load disturbance isapplied by controlling the opening area of servo valve whichis installed in a meter outline of load cylinder
As shown in Figure 18 the optimal PID and optimalantiwindup PID control systems do not achieve robustnessto the parameter change and load disturbance In spite of theload disturbance and saturation of the BLDC motor in theposition control system for EHA the adaptive antiwindupPID sliding mode control system has a better performanceand robustness than the optimal PID and optimal antiwindupPID control systems such that the adaptive antiwindup PID
sliding mode control system recovers the parameter changeand external disturbance in about 09 sec with a small over-shootThe time-domain quantitative performance indicatorsare summarized in Table 5 for optimal PID antiwindup PIDand adaptive antiwindup PID sliding mode control systemswith load disturbance The list of terms are represented inTable 6
6 Conclusion
This paper discussed the application of the optimal PIDcontroller with optimal control gains using the optimizationtoolbox ofMATLABSimulink to the position control systemof EHA in order to understand the basic performancecharacteristics of the system In experiment with optimal PIDcontroller large overshoot due to saturation of electric motoris observed
14 The Scientific World Journal
0 05 1 15 2 25 30
5
10
15
20
25
30
35
Position referenceOptimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(b) Position errors
0 05 1 15 2 25 30
2
4
6
8
10
Load
forc
e (kN
)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(c) Load force
Figure 18 Performances of optimal PID antiwindup PID and adaptive antiwindup PID sliding mode control systems for EHA with loaddisturbance
Table 5 Comparison of the performance of optimal PID optimalantiwindup PID and adaptive antiwindup PID slidingmode controlsystems with load disturbance
Performance OptimalPID
Optimalantiwindup PID
Adaptive antiwindupPID sliding mode
Overshoot 45 39 12Settling time 38 sec 18 sec 08 sec
In order to achieve the desirable performance of EHAposition control system optimal antiwindup PID controller
and adaptive antiwindup PID sliding mode controller arealso applied to control the position of EHA systems Inthe process of robust control system design mathematicalmodeling was carried out based on theoretical analysisand the simple third-order nominal model was derivedThe system parameters of the simple second-order nominalmodel were identified by the signal compression method
Based on the experimental results and the time-domainquantitative performance indicators the performance of theEHA position control system can be improved and robustto the load disturbance parameter variation and system
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
![Page 13: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/13.jpg)
The Scientific World Journal 13
0 5 10 15 20 25 300
400
800
1200
1600
2000
Bulk
mod
ulus
(MPa
)
Pressure (MPa)
Contained air ratio ()001
110
Figure 16 Example of the relationship between pressure and effective bulk modulus [12 13]
0 05 1 15 2 25 30123456789
101112
Pres
sure
(MPa
)
Time (s)
Pressure at port number 1Pressure at port number 2
Figure 17 Pressure variations of optimal PID position control system for EHA with load disturbance
In order to investigate robustness to the lumped systemuncertainties such as varying parameters and modeling errorand load disturbance the performances of the three-positioncontrollers of EHA system are compared in experiments byapplying load disturbance The experiments are conductedwith 20mm position reference and the load disturbance isapplied by controlling the opening area of servo valve whichis installed in a meter outline of load cylinder
As shown in Figure 18 the optimal PID and optimalantiwindup PID control systems do not achieve robustnessto the parameter change and load disturbance In spite of theload disturbance and saturation of the BLDC motor in theposition control system for EHA the adaptive antiwindupPID sliding mode control system has a better performanceand robustness than the optimal PID and optimal antiwindupPID control systems such that the adaptive antiwindup PID
sliding mode control system recovers the parameter changeand external disturbance in about 09 sec with a small over-shootThe time-domain quantitative performance indicatorsare summarized in Table 5 for optimal PID antiwindup PIDand adaptive antiwindup PID sliding mode control systemswith load disturbance The list of terms are represented inTable 6
6 Conclusion
This paper discussed the application of the optimal PIDcontroller with optimal control gains using the optimizationtoolbox ofMATLABSimulink to the position control systemof EHA in order to understand the basic performancecharacteristics of the system In experiment with optimal PIDcontroller large overshoot due to saturation of electric motoris observed
14 The Scientific World Journal
0 05 1 15 2 25 30
5
10
15
20
25
30
35
Position referenceOptimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(b) Position errors
0 05 1 15 2 25 30
2
4
6
8
10
Load
forc
e (kN
)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(c) Load force
Figure 18 Performances of optimal PID antiwindup PID and adaptive antiwindup PID sliding mode control systems for EHA with loaddisturbance
Table 5 Comparison of the performance of optimal PID optimalantiwindup PID and adaptive antiwindup PID slidingmode controlsystems with load disturbance
Performance OptimalPID
Optimalantiwindup PID
Adaptive antiwindupPID sliding mode
Overshoot 45 39 12Settling time 38 sec 18 sec 08 sec
In order to achieve the desirable performance of EHAposition control system optimal antiwindup PID controller
and adaptive antiwindup PID sliding mode controller arealso applied to control the position of EHA systems Inthe process of robust control system design mathematicalmodeling was carried out based on theoretical analysisand the simple third-order nominal model was derivedThe system parameters of the simple second-order nominalmodel were identified by the signal compression method
Based on the experimental results and the time-domainquantitative performance indicators the performance of theEHA position control system can be improved and robustto the load disturbance parameter variation and system
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
![Page 14: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/14.jpg)
14 The Scientific World Journal
0 05 1 15 2 25 30
5
10
15
20
25
30
35
Position referenceOptimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
Pisto
n di
spla
cem
ent (
mm
)
Time (s)
(a) Step responses
0 05 1 15 2 25 3minus1
minus08
minus06
minus04
minus02
0
02
04
06
08
1
Posit
ion
erro
r (m
m)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(b) Position errors
0 05 1 15 2 25 30
2
4
6
8
10
Load
forc
e (kN
)
Time (s)
Optimal PIDOptimal antiwindup PIDAdaptive antiwindup PID sliding mode
(c) Load force
Figure 18 Performances of optimal PID antiwindup PID and adaptive antiwindup PID sliding mode control systems for EHA with loaddisturbance
Table 5 Comparison of the performance of optimal PID optimalantiwindup PID and adaptive antiwindup PID slidingmode controlsystems with load disturbance
Performance OptimalPID
Optimalantiwindup PID
Adaptive antiwindupPID sliding mode
Overshoot 45 39 12Settling time 38 sec 18 sec 08 sec
In order to achieve the desirable performance of EHAposition control system optimal antiwindup PID controller
and adaptive antiwindup PID sliding mode controller arealso applied to control the position of EHA systems Inthe process of robust control system design mathematicalmodeling was carried out based on theoretical analysisand the simple third-order nominal model was derivedThe system parameters of the simple second-order nominalmodel were identified by the signal compression method
Based on the experimental results and the time-domainquantitative performance indicators the performance of theEHA position control system can be improved and robustto the load disturbance parameter variation and system
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
![Page 15: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/15.jpg)
The Scientific World Journal 15
Table 6 List of terms
Notation Description UnitA Pressurized area of hydraulic cylinder of EHA m2
119861 Viscous friction coefficient Nmsec119862119879
Equivalent leakage coefficient m3secPa119863119901
Pump displacement m3rad119890 Position error mm119894 Current Arms119870pipe Pipe coefficient relating pressure drop to flow Pam6sec2
119870119904
Angular velocity to voltage gain mdash119870119901
Proportional control gain mdash119870119894
Integral control gain mdash119870119889
Differential control gain mdash119896119886
Antiwindup gain mdash1198961
1198962
1198963
119863 119870 120574 Positive design parameters of adaptive PID sliding mode controller mdash119870119898
1198791
1198791198981 1198791198982
Parameters of dynamic model for the BLDC motor with controller mdashL Internal leakage coefficient of the cylinder m3PasecM Mass load of position control test rig of EHA N1199011
1199012
Cylinder inletoutlet chamber pressure Pa119901pipe Pressure drop of pipe between the pump and the cylinder Pa1198761
1198762
Cylinder inletoutlet flow m3sec119904 Laplace operator mdash119879119898
Torque of BLDC motor Nm(radsec)119879119904
Sampling time sec119881119886
119881119887
Volumes of inletoutlet pipe and cylinder chamber m3
1198810
Mean volume of pipe and cylinder chamber m3
V119890
Voltage signal of error for angular velocity of BLDC motor VV119903
Voltage signal of reference angular velocity of BLDC motor VV120596
Voltage signal of angular velocity V119909 Cylinder displacement m119910119889
step(119905) Desired step response of the optimal PID and antiwindup PID control system mdash119910step(119905) Step response by the identified transfer function mdash120573119890
Effective bulk modulus Pa120596119901
Pump angular velocity radsec120577 Sliding surface mdash120585 Pump cross port leakage coefficient m3Pasec
uncertainty such as saturation of electric motor by using theadaptive antiwindup PID sliding mode controller
References
[1] J-MZheng S-D Zhao and S-GWei ldquoFuzzy iterative learningcontrol of electro-hydraulic servo system for SRM direct-drive volume control hydraulic pressrdquo Journal of Central SouthUniversity of Technology vol 17 no 2 pp 316ndash322 2010
[2] J-M Zheng S-D Zhao and S-G Wei ldquoApplication of self-tuning fuzzy PID controller for a SRM direct drive volumecontrol hydraulic pressrdquoControl Engineering Practice vol 17 no12 pp 1398ndash1404 2009
[3] D K Pitipongsa Guansak and W Po-Ngaen ldquoTwo layer fuzzygeneralized Maxwell-slip compensator in direct drive servohydraulic systemrdquo inAppliedMechanics andMaterials pp 420ndash427 2012
[4] Y Cao X Y Tian GQWuQM Li andYHWu ldquoSimulationexperiment of roll bending machine in valveless servo systemrdquoAdvanced Materials Research vol 619 pp 410ndash414 2012
[5] Y Chinniah R Burton and S Habibi ldquoFailure monitoringin a high performance hydrostatic actuation system using theextended Kalman filterrdquo Mechatronics vol 16 no 10 pp 643ndash653 2006
[6] Y Chinniah R Burton S Habibi and E Sampson ldquoIdentifi-cation of the nonlinear friction characteristics in a hydraulicactuator using the extended Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 32 no 2 pp121ndash136 2008
[7] Y Chinniah S Habibi R Burton and E Sampson ldquoParameteridentification in a high performance hydrostatic actuationsystem using the Unscented Kalman filterrdquo Transactions of theCanadian Society for Mechanical Engineering vol 30 no 3 pp375ndash389 2006
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
![Page 16: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/16.jpg)
16 The Scientific World Journal
[8] K Rongjie J Zongxia W Shaoping and C Lisha ldquoDesign andsimulation of electro-hydrostatic actuator with a built-in powerregulatorrdquoChinese Journal of Aeronautics vol 22 no 6 pp 700ndash706 2009
[9] HMKim SH Park JH Song and J S Kim ldquoRobust positioncontrol of electro-hydraulic actuator systems using the adaptiveback-stepping control schemerdquo Journal of Systems and ControlEngineering vol 224 no 6 pp 737ndash746 2010
[10] Y Lin Y Shi and R Burton ldquoModeling and robust discrete-time sliding-mode control design for a fluid power electrohy-draulic actuator (EHA) systemrdquo IEEEASME Transactions onMechatronics vol 18 no 1 pp 1ndash10 2013
[11] HM Kim S H Park J M Lee and J S Kim ldquoA robust controlof electro hydrostatic actuator using the adaptive back-steppingscheme and fuzzy neural networksrdquo International Journal ofPrecision Engineering andManufacturing vol 11 no 2 pp 227ndash236 2010
[12] J Kajaste H Kauranne A Ellman and M Pietola ldquoExperi-mental validation of differentmodels for effective bulkmodulusof hydraulic fluidrdquo in Proceedings of the 9th ScandinavianInternational Conference on Fluid Power (SICFP rsquo05) p 16Linkoping Sweden 2005
[13] K Sunghun and M Hubertus Measurement of Effective BulkModulus for Hydraulic Oil at Low Pressure vol 134 ETATS-UNIS American Society of Mechanical Engineers New YorkNY USA 2012
[14] M A El Sayed and S Habibi ldquoInner-loop control for electro-hydraulic actuation systemsrdquo Journal of Dynamic SystemsMeasurement and Control vol 134 no 1 2012
[15] S Habibi and A Goldenberg ldquoDesign of a new high perfor-mance electrohydraulic actuatorrdquo IEEEASME Transactions onMechatronics vol 5 no 2 pp 158ndash164 2000
[16] M Pachter C H Houpis and K Kang ldquoModelling and controlof an electro-hydrostatic actuatorrdquo International Journal ofRobust and Nonlinear Control vol 7 no 6 pp 591ndash608 1997
[17] SWang R Burton and S Habibi ldquoSlidingmode controller andfilter applied to an electrohydraulic actuator systemrdquo Journal ofDynamic SystemsMeasurement andControl vol 133 no 2 2011
[18] S Wang S Habibi and R Burton ldquoSliding mode control for anelectrohydraulic actuator systemwith discontinuous non-linearfrictionrdquo Journal of Systems and Control Engineering vol 222no 8 pp 799ndash815 2008
[19] K K Ahn and Q T Dinh ldquoSelf-tuning of quantitative feedbacktheory for force control of an electro-hydraulic test machinerdquoControl Engineering Practice vol 17 no 11 pp 1291ndash1306 2009
[20] S H Cho and R Burton ldquoPosition control of high performancehydrostatic actuation system using a simple adaptive control(SAC) methodrdquoMechatronics vol 21 no 1 pp 109ndash115 2011
[21] H E Merritt Hydrostatic Control Systems Wiley InterscienceNew York NY USA 1967
[22] S R Habibi and R Burton ldquoParameter identification fora high-performance hydrostatic actuation system using thevariable structure filter conceptrdquo Journal of Dynamic SystemsMeasurement and Control vol 129 no 2 pp 229ndash235 2007
[23] J Y Oh G-H Jung G-H Lee Y-J Park and C-S SongldquoModeling and characteristics analysis of single-rod hydraulicsystemusing electro-hydrostatic actuatorrdquo International Journalof Precision Engineering and Manufacturing vol 13 no 8 pp1445ndash1451 2012
[24] N Aoshima ldquoMeasurement of nonlinear vibration by signalcompression methodrdquo Journal of the Acoustical Society ofAmerica vol 76 no 3 pp 794ndash801 1984
[25] G P Liu and S Daley ldquoOptimal-tuning nonlinear PID controlof hydraulic systemsrdquo Control Engineering Practice vol 8 no 9pp 1045ndash1053 2000
[26] S-U Lee and P H Chang ldquoThe development of anti-windupscheme for time delay control with switching action using inte-gral sliding surfacerdquo Journal of Dynamic Systems Measurementand Control vol 125 no 4 pp 630ndash638 2003
[27] M Yokoyama G-N Kim and M Tsuchiya ldquoIntegral slidingmode control with anti-windup compensation and its applica-tion to a power assist systemrdquo Journal of Vibration and Controlvol 16 no 4 pp 503ndash512 2010
[28] M Yokoyama Y Tohta and K Saitoh ldquoA design method ofsliding mode controller for servo-systems subject to actuatorsaturationrdquo JSME International Journal Series C vol 46 no 3pp 960ndash966 2003
[29] I Eker ldquoSecond-order sliding mode control with PI slidingsurface and experimental application to an electromechanicalplantrdquo Arabian Journal for Science and Engineering vol 37 no7 pp 1969ndash1986 2012
[30] I Eker ldquoSecond-order sliding mode control with experimentalapplicationrdquo ISA Transactions vol 49 no 3 pp 394ndash405 2010
[31] I Eker ldquoSliding mode control with PID sliding surface andexperimental application to an electromechanical plantrdquo ISATransactions vol 45 no 1 pp 109ndash118 2006
[32] I Eker and S A Akınal ldquoSliding mode control with integralaugmented sliding surface design and experimental applicationto an electromechanical systemrdquo Electrical Engineering vol 90no 3 pp 189ndash197 2008
[33] J J E Slotine and W Li Applied Nonlinear Control PearsonEducation Upper Saddle River NJ USA 1991
[34] M Krstic I Kanellakopoulos and P Kokotovic Nonlinear andAdaptive Control Design Wiley Interscience New York NYUSA 1995
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
![Page 17: Research Article Design and Experimental Evaluation of a ...position control system, a number of control strategies have been applied and investigated by many researchers. Some of](https://reader035.fdocuments.in/reader035/viewer/2022071420/6118bd4a9debcb0c5c41400e/html5/thumbnails/17.jpg)
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of