Slide 1 Exceptional Process Control Opportunities - Smart and Wireless Instrumentation, Valves, PID,...

Exceptional Process Control Exceptional Process Control Opportunities Opportunities - Smart and Wireless - Smart and Wireless Instrumentation, Valves, PID, and TuningInstrumentation, Valves, PID, and Tuning

Exceptional Process Control Exceptional Process Control Opportunities Opportunities - Smart and Wireless - Smart and Wireless Instrumentation, Valves, PID, and TuningInstrumentation, Valves, PID, and Tuning Experitec Kansas City Technology Open House Seminar – March 26, 2010

http://www.modelingandcontrol.com/

[File Name or Event]Emerson Confidential27-Jun-01, Slide 2 Slide 2

WelcomeWelcome WelcomeWelcome Gregory K. McMillan

– Greg is a retired Senior Fellow from Solutia/Monsanto and an ISA Fellow. Presently, Greg contracts as a consultant in DeltaV R&D via CDI Process & Industrial. Greg received the ISA “Kermit Fischer Environmental” Award for pH control in 1991, the Control Magazine “Engineer of the Year” Award for the Process Industry in 1994, was inducted into the Control “Process Automation Hall of Fame” in 2001, and was honored by InTech Magazine in 2003 as one of the most influential innovators in automation. Greg is the author of numerous books on process control, his most recent being Essentials of Modern Measurements and Final Elements for the Process Industry. Greg has been the monthly “Control Talk” columnist for Control magazine since 2002. Greg’s expertise is available on the web site: http://www.modelingandcontrol.com/


Newest Book - The Latest on Smart and Newest Book - The Latest on Smart and Wireless Instrumentation Wireless Instrumentation

Newest Book - The Latest on Smart and Newest Book - The Latest on Smart and Wireless Instrumentation Wireless Instrumentation

Royalties are donated to theUniversity of Texas Research Campus for Energy and Environmental Resources for Development of WirelessInstrumentation and Control


Top Ten Ways to Make Process Control EnticingTop Ten Ways to Make Process Control EnticingTop Ten Ways to Make Process Control EnticingTop Ten Ways to Make Process Control Enticing

(10) Travel programs focusing on the process control systems of cruise ships

(9) Sci-fi flicks devoted to the process control systems in star ships

(8) Reality shows where teams compete to improve process control performance

(7) Entourage shows where groupies use process control to keep their star from self-destruction

(6) Sport analysis programs where commentators and listeners talk about the dynamics and feedforward control opportunities in football

(5) Robot movies where advanced parallel processing robots optimize plants

(4) Detective shows where a special investigator with cute compulsive obsessive habits and an incredibly keen mind for details solves mysterious process control problems

(3) “Who done it” novels where the culprit is a bad acting control valve

(2) Web video with cute animal antics in the foreground and engineers talking about process control opportunities in the background

(1) “Cash for clunkers” programs to replace inefficient old distributed control systems, transmitters, and valves


Fundamentals - Effect of Step Size on Fundamentals - Effect of Step Size on Small Valve ResponseSmall Valve Response

Fundamentals - Effect of Step Size on Fundamentals - Effect of Step Size on Small Valve ResponseSmall Valve Response


Control Valve Deadband and Stick-SlipControl Valve Deadband and Stick-SlipControl Valve Deadband and Stick-SlipControl Valve Deadband and Stick-Slip

dead band

Deadband

Stick-Slip is worse near closed position

Signal (%)

0

Stroke (%) Digital positioner

will force valve shut at 0% signal

Pneumatic positionerrequires a negative % signal to close valve

Deadband (backlash) and stick-slip (sticktion) is greatest near the closed position

Deadband is 5% - 50%without a positioner !


Installed Characteristic (Linear Trim)Installed Characteristic (Linear Trim)Installed Characteristic (Linear Trim)Installed Characteristic (Linear Trim)

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

Inherent Characteristic

Installed Characteristic 1




Valve pressure drop ratio (PR)for installed characteristic:

Characteristic 1: PR 0.5 Characteristic 2: PR 0.25Characteristic 3: PR 0.125Characteristic 4: PR 0.0625


Installed Characteristic (Equal Percentage Trim)Installed Characteristic (Equal Percentage Trim)Installed Characteristic (Equal Percentage Trim)Installed Characteristic (Equal Percentage Trim)

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

Inherent Characteristic





Valve pressure drop ratio (PR)for installed characteristic:

Characteristic 1: PR 0.5 Characteristic 2: PR 0.25Characteristic 3: PR 0.125Characteristic 4: PR 0.0625


Limit Cycle in Flow Loop Limit Cycle in Flow Loop from Valve Stick-Slipfrom Valve Stick-Slip

Limit Cycle in Flow Loop Limit Cycle in Flow Loop from Valve Stick-Slipfrom Valve Stick-Slip

Controller Output (%)Saw Tooth Oscillation

Process Variable (kpph)Square Wave Oscillation


Limit Cycle in Level Loop Limit Cycle in Level Loop from Valve Deadbandfrom Valve Deadband

Limit Cycle in Level Loop Limit Cycle in Level Loop from Valve Deadbandfrom Valve Deadband

Manipulated Flow (kpph)Clipped Oscillation

Controller Output (%)Rounded Oscillation

Level (%)


Real Rangeability Real Rangeability Real Rangeability Real Rangeability Minimum fractional flow coefficient for a linear trim and stick-slip:

Minimum fractional flow coefficient for an equal percentage trim and stick-slip:

Minimum controllable fractional flow for installed characteristic and stick-slip:

Cxmin minimum flow coefficient expressed as a fraction of maximum (dimensionless)Pr valve pressure drop ratio (dimensionless) Qxmin minimum flow expressed as a fraction of the maximum (dimensionless)Rv rangeability of control valve (dimensionless) R range of the equal percentage characteristic (e.g. 50)Xvmin maximum valve stroke (%)Sv stick-slip near closed position (%)

maxmin

v

vx X

SC

]1[

minmax

v

vv

X

S

x RC

2min

minmin

)1( xRR

xx

CPP

CQ

min

1

xv QR


Best Practices to Improve Valve PerformanceBest Practices to Improve Valve PerformanceBest Practices to Improve Valve PerformanceBest Practices to Improve Valve Performance Actuator, valve, and positioner package from a control valve

manufacturer Digital positioner tuned for valve package and application Diaphragm actuators where application permits (large valves and high

pressure drops may require piston actuators) Sliding stem (globe) valves where size and fluid permit (large flows and

slurries may require rotary valves) Next best is V-ball or contoured butterfly valve with rotary actuator and positioner

Low packing, sealing, and seating friction Booster(s) on positioner output(s) for large valves on fast loops (e.g.,

compressor anti-surge control) Valve sizing for a throttle range that provides good linearity [4]:

o 5% to 75% (sliding stem globe),

o 10o to 60o (v-ball)

o 25o to 45o (conventional butterfly)

o 5o to 65o (contoured and toothed butterfly)

Online diagnostics and step response tests for small changes in signal Dynamic reset limiting (FRSPID_OPTS) using digital positioner feedback


Volume Booster with Integral BypassVolume Booster with Integral Bypass(Furnace Pressure and Surge Control)(Furnace Pressure and Surge Control)

Signal from Positioner

Air Supply fromFilter-Regulator

Air Loadingto Actuator

Adjustable BypassNeedle Valve


Port A

Port B

Supply

ZZ

ZZ

ZZ

Z

Control Signal

Digital Valve Controller

Must be functionally testedbefore commissioning!

1:1

Bypass

VolumeBooster

Open bypass justenough to ensurea non-oscillatory fast response

Air Supply

High CapacityFilter Regulator

Increase air line size

Increase connection size

Terminal Box

Booster and Positioner SetupBooster and Positioner Setup(Furnace Pressure and Surge Control)(Furnace Pressure and Surge Control)


Open Loop Backup Configuration

SP_Rate_DN and SP_RATE_UP used to insure fast getaway and slow approach

Open loop backup used for prevention of compressor surge and RCRA pH violation

Open Loop Backup ConfigurationOpen Loop Backup Configuration


PID Controller Disturbance ResponsePID Controller Disturbance Response


Open Loop Backup Disturbance ResponseOpen Loop Backup Disturbance Response

Open Loop Backup


Conductivity Kicker for EvaporatorConductivity Kicker for Evaporator

Rise in conductivity

Flow cutback via kicker


Mixer

AttenuationTank

AY

AT

middle selector

AYsplitter

AT

FT

FT

AT

AY

ATAT AT

AY

ATAT AT

Mixer

AY

FT

Stage 2Stage 1

middle selector

Wastemiddle selectorRCAS RCAS

splitter

AY

filter

AYROUT

kickerAC-1 AC-2

MPC-2

MPC-1

pH Kicker for Waste TreatmentpH Kicker for Waste Treatment


Question: Which MeasurementQuestion: Which MeasurementQuestion: Which MeasurementQuestion: Which Measurement Removes the most common nonlinearity in a control loop? Compensates for pressure disturbances? Is used in most cascade control systems? Is used in most feedforward control systems? Is essential to close the material balance for a process? Makes the following advanced control tools more effective?

– Model Predictive Control (DeltaV PredictPro)

– Adaptive Control (DeltaV Insight)

– Neural Network Predictions (DeltaV Neural)

– Projections to Latent Structures Predictions (DeltaV Analytics)

– Dynamic Models (MIMIC Advanced Modeling)

Answer: FlowAnswer: Flowhttp://www.isa.org/InTechTemplate.cfm?template=/ContentManagement/ContentDisplay.cfm&ContentID=81073


Ratio Control ExamplesRatio Control ExamplesRatio Control ExamplesRatio Control Examples Coolant/Feed flow ratio for crystallizer, cooler, extruder, or exothermic reactor

temperature control Steam/Feed flow ratio for distillation column, evaporator, heater, dryer, or endothermic

reactor temperature control Distillate/Feed or reflux/feed flow ratio for column temperature control Reagent/Feed flow ratio for pH control Reactant/Reactant flow ratio for continuous and fed-batch reactor control Catalyst/Reactant flow ratio for continuous and fed-batch reactor control Makeup/Recycle flow ratio for continuous and fed-batch reactor control Purge/Product flow ratio for continuous and perfusion process contaminant control Stock/Dilution flow ratio control for stock consistency control Additive/Feed flow ratio for blend control (e.g., percent solids) Air/Fuel flow ratio for boiler or furnace combustion control (oxygen control) Feedwater/Steam flow ratio for boiler drum level control (three element control) Blowdown/Feedwater flow ratio for boiler total dissolved solids (conductivity control) Supply/Demand flow ratio for header pressure control Vent/Demand flow ratio for compressor surge control Lime/Liquor flow ratio for slaker control

http://www.modelingandcontrol.com/2009/03/what_have_i_learned_-_ratio_co.html

The best setpoint and process gain is the operating point and slope on a plot of composition, pH and temperature versus a flow ratio


Coriolis Flow Measurement OpportunitiesCoriolis Flow Measurement OpportunitiesCoriolis Flow Measurement OpportunitiesCoriolis Flow Measurement Opportunities Live Process Flow Diagrams (PFD) for Plant Performance Analysis

– The first document you have on a project is typically a process flow diagram (PFD). The PFD defines the process. It is the ultimate source of info and sets the plant performance and design.

– What if a plant had a live online PFD? What if we had temperature, pressure, mass flow, and inferential measurements of the composition in every important process stream?

– What if a plant had online process metrics for yield, efficiency, and production from live PFDs Reactant, Catalyst, Recycle, Dilution, and Reagent Ratio Control

– True mass flow independent of temperature, density, composition, phases, viscosity, velocity, and installation enables tight control of component concentrations for reaction and neutralization

Crystallizer, Evaporator, and Column Product Composition Control– Inferential measurement of concentrations or percent solids in feed and product streams enable

feedback and feedforward control of composition by manipulation of heat input or temperature Batch Charge Control

– Coriolis meters can potentially provide more accurate batch charges than weigh tanks because Coriolis meters retain a better long term installed accuracy than load cells since Coriolis does not suffer from drift or installation effects and doesn’t require periodic calibration checks

Fermentation Alcohol Yield Optimization– Measurement and totalization of carbon dioxide vent flow provides an inferential measurement

of conversion of sugars to alcohol that can be used to optimize batch cycle time or efficiency Centrifuge and Dryer Moisture Control

– Measurement of percent solids in feed enables feedforward controlhttp://www.modelingandcontrol.com/mt/mt-search.cgi?IncludeBlogs=1&search=Live+Process+Flow

http://www.modelingandcontrol.com/EssentialBookCoriolisExcerpt.pdf


Radar Level Measurement OpportunitiesRadar Level Measurement OpportunitiesRadar Level Measurement OpportunitiesRadar Level Measurement Opportunities Raw material and product storage tanks require the best level

measurement accuracy, when used in the calculations for:– Inventory accounting and optimization– Custody transfer– Batch charge (rate of change of level)– Continuous feed rates (rate of change of level)– Material balances (process holdup)

Column distillate receivers require the best level measurement resolution, sensitivity, and repeatability for direct material balance control

– a small change in level must quickly translate to a change in reflux flow to balance a change in vapor flow. This inherent self-regulation provides some internal reflux control and helps decouple the energy balance from the material balance.

– When the temperature loop makes a change in the distillate flow, the change in controller output has no effect on column temperature until the overhead receiver controller makes a change in the reflux flow

Crystallizers and reactors (batch and continuous) require the best level measurement accuracy to control and maximize crystallization and reaction

– Continuous feed rate and batch cycle time set percent conversion for a given level– Level sets production rate for a given residence time and batch cycle time

http://www.isa.org/InTechTemplate.cfm?template=/ContentManagement/ContentDisplay.cfm&ContentID=81073


m m

m

m

Measurement Filter (Transmitter Damping) EffectMeasurement Filter (Transmitter Damping) EffectMeasurement Filter (Transmitter Damping) EffectMeasurement Filter (Transmitter Damping) Effect

For compressor, incinerator pressure, and polymer pressurecontrol it is critical to make sure transmitter is fast enough!

http://www.modelingandcontrol.com/2007/04/analog_control_holdouts.html


f

oof

TAA

2*

Attenuation of Oscillation Amplitude by Transmitter Damping or Signal Filters:

When a measurement or signal filter time (f) becomes the largest timeconstant in the loop, the above equation can be solved for (Ao) to get the amplitude of the original process variability from the filtered amplitude (A f)

Transmitter Damping and Signal Filtering EffectTransmitter Damping and Signal Filtering EffectTransmitter Damping and Signal Filtering EffectTransmitter Damping and Signal Filtering Effect


Sample Time Table Typical Values Sample Time Table Typical Values Sample Time Table Typical Values Sample Time Table Typical Values

Practical and Ultimate sample times are for conservative and aggressive tuning, respectively

Type of Process Loop Process Deadtime

Process Time Constant

Practical Sample Time

Ultimate Sample Time

Liquid Flow 0.05 - 0.5 sec 0.5 - 5 sec 2 sec 0.1 sec

Gas Flow 0.1 - 0.5 sec 1 - 10 sec 1 sec 0.1 sec

Liquid Pressure* 0.05 - 0.5 sec 0.2 - 1 sec 0.1 sec 0.02 sec

Column Pressure! 1 - 10 sec 10 - 100 sec 10 sec 2 sec

Furnace Pressure* 0.1 - 0.5 sec 0.2 - 20 sec 0.1 sec 0.02 sec

Vessel Pressure! 0.2 - 1 sec 10 - 100 sec 10 sec 1 sec

Surge Control 0.05 - 0.5 sec 0.2 - 10 sec 0.1 sec 0.02 sec

Liquid Level! 0.05 - 0.5 sec 10 - 100000 min 300 sec 60 sec

Exchanger Temperature 0.2 - 2 min 0.5 - 5 min 10 sec 2 sec

Batch Temperature! 1 - 10 min 5 - 100000 min 150 sec 30 sec

Runaway Temperature!! 0.5 - 5 min 1 - 100 min 10 sec 5 sec

Column Temperature 2 - 100 min 10 - 1000 min 300 sec 60 sec

Furnace Temperature 0.2 - 2 min 0.5 - 5 min 10 sec 2 sec

Vessel Temperature 1 - 10 min 5 - 50 min 150 sec 30 sec

Column Composition 1 - 50 min 10 - 1000 min 300 sec 60 sec

Furnace Oxygen 0.2 - 1 min 0.2 - 1 min 10 sec 2 sec

Vessel Composition 0.5 - 5 min 5 - 50 min 150 sec 30 sec

Inline (Static Mixer) pH 2 - 10 sec 2 - 10 sec 2 sec 0.5 sec

Vessel pH 0.5 - 5 min 1 - 50 min 30 sec 5 sec


Sample Time Guideline NotesSample Time Guideline NotesSample Time Guideline NotesSample Time Guideline Notes The term “sample time” is used in the broadest sense as the time between updates in sampled data from

digital measurements and controllers and from analyzers The table should be useful for determining whether DCS scan or module execution times, wireless communication time intervals, model predictive control execution time, and at-line analyzer cycle time will affect control system performance.

* - denotes loop uses a variable speed drive with a negligible dead time, deadband, and resolution limit as the final element. If a control valve or damper is used for these loops, you can multiply the sample times for asterisked items by a factor of 5.

! - denotes an integrating response whose integrating process gain is the inverse of the process time constant shown

!! - denotes a runaway response that can accelerate and reach a point of no return For surge control, it assumed that a volume booster has been added to the each of the positioner outputs

to reduce the pre-stroke dead time to less than 0.2 seconds. A valve with excessive sticktion and backlash will add significant deadtime to the response to unmeasured disturbances that deteriorates the ultimate limit to possible performance.

For inline (static mixer) pH control, the largest time constant comes from the sensor lag or the process variable filter time with a nominal value of 5 seconds.

For the vessel pH control it is assumed the mixing time is less than 30 sec and the reagent delivery time delay is negligible by injection of the reagent into a recirculation line just before it enters the vessel. The lower value for the time constant is for a set point on a steep titration curve that cause the pH to move much faster than for a linear response. The response can look like a runaway as the pH accelerates through the neutral region.

For level control set point changes, the deadtime observed is usually about 10 times larger than the actual process deadtime due to level measurement sensitivity limits and noise. For unmeasured disturbances the deadtime observed is often about 20 times larger than the actual process deadtime because of the amount of time it takes the controller output to work through the resolution limit and deadband of the control valve.

http://www.modelingandcontrol.com/2009/09/largest_opportunities_in_proce_1.html


Advances in Smart MeasurementsAdvances in Smart MeasurementsAdvances in Smart MeasurementsAdvances in Smart Measurements

Technological advances in sensing element technology Integration of multiple measurements Compensation of application and installation effects Online device diagnostics Digital signals with embedded extensive user selected information Wireless communication

The out of the box accuracy of modern industrial instrumentation has improved by an order of magnitude. Consider the most common measurement device, the differential pressure transmitter (DP). The 0.25% accuracy of an analog electronic DP has improved to 0.025% accuracy for a smart microprocessor based d/p. Furthermore, the analog DP accuracy often deteriorated to 2% when it was moved from the nice bench top setting to service outdoors in a nasty process with all its non-ideal effects of installation, process, and ambient effects [1][16]. A smart d/p with its integrated compensation for non-ideal effects will stay close to its inherent 0.025% accuracy. Additionally a smart DP takes 10 years to drift as much as the analog d/p did in 1 year.


(10) Reliable from day one

(9) Always on the job

(8) Low maintenance - minimal grooming, clothing, and entertainment

(7) Many programmable features

(6) Stable

(5) Short settling time

(4) No frills or extraneous features

(3) Relies on feedback

(2) Good response to commands and amenable to real time optimization

(1) Readily tuned

Top Ten Reasons Why an Automation Engineer Top Ten Reasons Why an Automation Engineer makes a Great Spouse or at Least a Wedding Gift makes a Great Spouse or at Least a Wedding Gift


FieldDevice

FieldDevice

FieldDevice

RouterDevice

RouterDevice

FieldDevice

FieldDevice

FieldDevice

GatewayDevice

Plant Automation Network

Plant Automation Application Host

Wireless HART

Handheld

Network Manager

WirelessHART Network TopologyWirelessHART Network TopologyWirelessHART Network TopologyWirelessHART Network Topology Wireless Field Devices

– Relatively simple - Obeys Network Manager– All devices are full-function (e.g., must route)

Adapters– Provide access to existing HART-enabled

Field Devices– Fully Documented, well defined requirements

Gateway and Access Points – Allows access to WirelessHART Network from

the Process Automation Network– Gateways can offer multiple Access Points for

increased Bandwidth and Reliability– Caches measurement and control values– Directly Supports WirelessHART Adapters– Seamless access from existing HART

Applications Network Manager

– Manages communication bandwidth and routing

– Redundant Network Managers supported – Often embedded in Gateway– Critical to performance of the network

Handheld– Supports direct communication to field device– For security, one hop only communication


WirelessHART FeaturesWirelessHART FeaturesWirelessHART FeaturesWirelessHART Features Wireless transmitters provide nonintrusive replacement and diagnostics Wireless transmitters automatically communicate alerts based on smart

diagnostics without interrogation from an automated maintenance system Wireless transmitters eliminate the questions of wiring integrity and termination Wireless transmitters eliminate ground loops that are difficult to track down Network manager optimizes routing to maximize reliability and performance Network manager maximizes signal strength and battery life by minimizing the

number of hops and preferably using routers and main (line) powered devices Network manager minimizes interference by channel hopping and blacklisting The standard WirelessHART capability of exception reporting via a resolution

setting helps to increase battery life WirelessHART control solution, keeps control execution times fast but a new value

is communicated as scheduled only if the change in the measurement exceeds the resolution or the elapsed time exceeds the refresh time

PIDPLUS and new communication rules can reduce communications by 96%


Wireless OpportunitiesWireless OpportunitiesWireless OpportunitiesWireless Opportunities Wireless temperatures and differential pressures for packed absorber and

distillation column hot spot and flow distribution analysis and control Wireless temperatures and differential pressures for fluidized bed reactor hot

spot and flow distribution analysis and control Wireless pressures to debottleneck piping systems, monitor process filter

operation, and track down the direction and source of pressure disturbances Wireless temperatures and flows to debottleneck coolant systems Wireless instrumentation to increase the mobility, flexibility, and maintainability

of lab and pilot plant experiments. Wireless pH and conductivity measurements for

– Selecting the best sensor technology for a wide range of process conditions– Eliminating measurement noise– Predicting sensor demise– Developing process temperature compensation– Developing inferential measurements of process concentrations– Finding the optimum sensor location

http://www.isa.org/InTechTemplate.cfm?template=/ContentManagement/ContentDisplay.cfm&ContentID=80886


Top Ten Signs of a WirelessHART AddictionTop Ten Signs of a WirelessHART AddictionTop Ten Signs of a WirelessHART AddictionTop Ten Signs of a WirelessHART Addiction

(10) You try to use the network manager to schedule the activities of your children

(9) You attempt to use RF patterns to explain your last performance review

(8) You use so much resource allocation in your network manager, you eat before you are hungry

(7) You propose your wireless device for the “Miss USA” contest

(6) You develop performance monitoring indices for your spouse

(5) You implement network management on your stock portfolio

(4) You carry pictures of your wireless device in your wallet

(3) You apply mesh redundancy and call three taxis to make sure you get home from your party

(2) You recommend a survivor show where consultants are placed in a plant with no staff or budget and are asked to add wireless to increase plant efficiency

(1) Your spouse has to lure you to bed by offering “expert options” for scheduling


Separations Research Program Separations Research Program University of Texas (UT) at AustinUniversity of Texas (UT) at AustinSeparations Research Program Separations Research Program

University of Texas (UT) at AustinUniversity of Texas (UT) at Austin

The Separations Research Program was established at the J.J. Pickle Research Campus in 1984

This cooperative industry/university program performs fundamental research of interest to chemical, biotechnological, petroleum refining, gas processing, pharmaceutical, and food companies.

CO2 removal from stack gas is a focus project for which WirelessHART transmitters are being installed


Wireless Lab pH and ConductivityWireless Lab pH and Conductivity(Inferential Measurements of Solvent and CO(Inferential Measurements of Solvent and CO22))Wireless Lab pH and ConductivityWireless Lab pH and Conductivity(Inferential Measurements of Solvent and CO(Inferential Measurements of Solvent and CO22))


Life Depends Upon Process ConditionsLife Depends Upon Process Conditions Life Depends Upon Process ConditionsLife Depends Upon Process Conditions

25 C 50 C 75 C 100 CProcess Temperature

Months

>100% increase in life from new glass designsfor high temperatures


New High Temperature Glass Stays FastNew High Temperature Glass Stays Fast New High Temperature Glass Stays FastNew High Temperature Glass Stays Fast

Glass electrodes get slow as they age. High temperatures cause premature aging


Smart Wireless pH ConfigurationSmart Wireless pH ConfigurationSmart Wireless pH ConfigurationSmart Wireless pH Configuration

Temperature Comp Parameters

Solution pH Temperature Correction

Isopotential Point Changeable for Special pH Electrodes

pH / ORP Selection

Preamplifier Location

Type of Reference Used

Ranging


Smart Wireless pH DashboardsSmart Wireless pH DashboardsSmart Wireless pH DashboardsSmart Wireless pH Dashboards


Wired Measurement Used in Control

Wireless Measurement Used in Control

The same dynamic control response was observed for SP changes

Filtering of 10 sec was applied to wired measurement, zero filtering for WirelessHART measurement.

Original plant PID tuning was used for both wired and wireless control

GAIN =0.12

RESET = 20.3

RATE = 0

Column Steam Flow Control Performance Column Steam Flow Control Performance Wired versus WirelessWired versus Wireless

Column Steam Flow Control Performance Column Steam Flow Control Performance Wired versus WirelessWired versus Wireless


The same dynamic control response was observed for SP changes

Original plant PID tuning was used for both wired and wireless control

GAIN=2.5

RESET=4

RATE=1 Same filtering

of 2 sec was applied to wireless and wired input

Wired Measurement Used in Control

Wireless Measurement Used in Control

Column Pressure Control Performance Column Pressure Control Performance Wired versus WirelessWired versus Wireless

Column Pressure Control Performance Column Pressure Control Performance Wired versus WirelessWired versus Wireless


Column Steam and Pressure Control Column Steam and Pressure Control Performance Wired versus WirelessPerformance Wired versus WirelessColumn Steam and Pressure Control Column Steam and Pressure Control Performance Wired versus WirelessPerformance Wired versus Wireless

Comparable control performance as measured by IAE was achieved using WirelessHART Measurements and DeltaV v11 PID option vs control with wired measurements and PID.

The number of measurement samples used in control with WirelessHART and v11 PID option versus Wired transmitter and PID was reduced by a factor of 10X for flow control and 6X for pressure control – accounting for differences in test duration.


Installation at Broadley JamesInstallation at Broadley JamesInstallation at Broadley JamesInstallation at Broadley James

Hyclone 100 liter Single Use Bioreactor (SUB)

Rosemount WirelessHART gateway and transmitters for measurement and control of pH and temperature. (pressure monitored)

BioNet lab optimized control system based on DeltaV


Elimination of Ground Noise Spikes by WirelessElimination of Ground Noise Spikes by WirelessElimination of Ground Noise Spikes by WirelessElimination of Ground Noise Spikes by Wireless

Wired pH ground noise spike

Temperature compensated wireless pH controlling at 6.9 pH set point

Incredibly tight pH control via 0.001 pH wireless resolution

setting still reduced the number of communications by 60%


Traditional and Wireless PID (PIDPLUS)Traditional and Wireless PID (PIDPLUS)Traditional and Wireless PID (PIDPLUS)Traditional and Wireless PID (PIDPLUS)

PID integral mode is restructured to provide integral action to match the process response in the elapsed time (reset time is set equal to process time constant)

PID derivative mode is modified to compute a rate of change over the elapsed time from the last new measurement value

PID reset and rate action are only computed when there is a new value

PID algorithm with enhanced reset and rate action is termed PIDPLUS

http://www.modelingandcontrol.com/repository/WirelessPrimeTime.pdf


Wireless Temperature Loop Test ResultsWireless Temperature Loop Test ResultsWireless Temperature Loop Test ResultsWireless Temperature Loop Test Results


Wireless pH Loop Test ResultsWireless pH Loop Test ResultsWireless pH Loop Test ResultsWireless pH Loop Test Results


Control Studies of pH Resolution and FeedforwardControl Studies of pH Resolution and Feedforward(Bioreactor batch running 500x real time)(Bioreactor batch running 500x real time)


Batch 3 Batch 4 Batch 3 Batch 4

Batches 1 and 2 have 0.00 pH resolution and standard PID

Batch 1 Batch 2 Batch 1 Batch 2Feedforward Feedforward

Feedforward Feedforward




Batches 9 and 10 have 30 sec x 500 refresh time and standard PID


Batches 11 and 12 have 30 sec x 500 refresh time and wireless PID

Control Studies of pH Refresh Time and FeedforwardControl Studies of pH Refresh Time and Feedforward (Bioreactor batch running 500x real time)(Bioreactor batch running 500x real time)

Control Studies of pH Refresh Time and FeedforwardControl Studies of pH Refresh Time and Feedforward (Bioreactor batch running 500x real time)(Bioreactor batch running 500x real time)


Continuous FF-NoStandard PID

Continuous FF-YesStandard PID

11 hr Sample FF-NoStandard PID

11 hr Sample FF-YesStandard PID

11 hr Sample FF-NoWireless PID

11 hr Sample FF-YesWireless PID

Batch 1 Batch 2 Batch 3 Batch 4 Batch 5 Batch 6

Glucose Concentration

Batch 1: Glucose Probe (Continuous - No Delay) + Feed Forward - No + Standard PIDBatch 2: Glucose Probe (Continuous - No Delay) + Feed Forward - Yes + Standard PIDBatch 3: Glucose Analyzer (11 Hr Sample Delay) + Feed Forward - No + Standard PIDBatch 4: Glucose Analyzer (11 Hr Sample Delay) + Feed Forward - Yes + Standard PIDBatch 5: Glucose Analyzer (11 Hr Sample Delay) + Feed Forward - No + Wireless PIDBatch 6: Glucose Analyzer (11 Hr Sample Delay) + Feed Forward - Yes + Wireless PID

Control Studies of Glucose Sample Time and Feedforward Control Studies of Glucose Sample Time and Feedforward (Bioreactor batch running 1000x real time)(Bioreactor batch running 1000x real time)

Control Studies of Glucose Sample Time and Feedforward Control Studies of Glucose Sample Time and Feedforward (Bioreactor batch running 1000x real time)(Bioreactor batch running 1000x real time)

x1000


Control Studies of Reset Factor & Wireless PID for Control Studies of Reset Factor & Wireless PID for Real Time Real Time IntegratingIntegrating Process Process (20 sec analyzer sample time)(20 sec analyzer sample time)

Control Studies of Reset Factor & Wireless PID for Control Studies of Reset Factor & Wireless PID for Real Time Real Time IntegratingIntegrating Process Process (20 sec analyzer sample time)(20 sec analyzer sample time)

Reset Factor = 0.5

Standard PID Standard PID Standard PID

Reset Factor = 1.0 Reset Factor = 2.0

Wireless PID Wireless PID Wireless PID

Reset Factor = 0.5 Reset Factor = 1.0 Reset Factor = 2.0

Improvement in stability is significant for any integrating process with analyzer delay


Control Studies of Lambda Factor & Wireless PID for Control Studies of Lambda Factor & Wireless PID for Real Time Real Time IntegratingIntegrating Process Process (20 sec analyzer sample time)(20 sec analyzer sample time)

Control Studies of Lambda Factor & Wireless PID for Control Studies of Lambda Factor & Wireless PID for Real Time Real Time IntegratingIntegrating Process Process (20 sec analyzer sample time)(20 sec analyzer sample time)

Lambda Factor = 1.5


Lambda Factor = 2.0 Lambda Factor = 2.5


Lambda Factor = 1.5 Lambda Factor = 2.0 Lambda Factor = 2.5

Improvement in stability is significant for any integrating process with analyzer delay


Control Studies of Reset Factor & Wireless PID for Control Studies of Reset Factor & Wireless PID for Real Time Real Time Self-RegulatingSelf-Regulating Process Process (40 sec analyzer sample time)(40 sec analyzer sample time)

Control Studies of Reset Factor & Wireless PID for Control Studies of Reset Factor & Wireless PID for Real Time Real Time Self-RegulatingSelf-Regulating Process Process (40 sec analyzer sample time)(40 sec analyzer sample time)





Improvement in stability and control is dramatic for any self-regulating process with analyzer delay


Control Studies of Lambda Factor & Wireless PID for Control Studies of Lambda Factor & Wireless PID for Real Time Real Time Self-Regulating Self-Regulating Process Process (40 sec analyzer sample time)(40 sec analyzer sample time) Control Studies of Lambda Factor & Wireless PID for Control Studies of Lambda Factor & Wireless PID for

Real Time Real Time Self-Regulating Self-Regulating Process Process (40 sec analyzer sample time)(40 sec analyzer sample time)





Improvement in stability and control is dramatic for any self-regulating process with analyzer delay


Conclusions from Wireless PID Control TestsConclusions from Wireless PID Control TestsConclusions from Wireless PID Control TestsConclusions from Wireless PID Control Tests Wireless PID and new communication rules can increase battery life Wireless pH eliminates spikes form ground noise Wireless PID provides tight control for set point changes Feedforward of ammonia formation rate and oxygen uptake rate (OUR) offers

significant improvement. OUR decouples interaction between pH and DO loops Wireless PIDPLUS dramatically improves the control and stability of any self-

regulating process with large measurement delay (sample delay). The wireless PID is a technological breakthrough for the use at-line analyzers for control

– The Wireless PIDPLUS set point overshoot is negligible for self-regulating processes with large sample delays if controller gain is less than the inverse of process gain

Wireless PIDPLUS is stable for self-regulating process with large sample delay if controller gain is less than twice the inverse of the process gain

– As the analyzer sample time decreases and approaches the module execution time, it is expected that the wireless PID behaves more like a standard PID

Wireless PIDPLUS significantly reduces the oscillations of integrating processes but the improvement is not as dramatic as for self-regulating processes

Integrating processes are much more sensitive than self-regulating processes to increases in sample time, decreases in reset time, and increases in gain

Detuned controllers (large Lambda Factors), makes loops less sensitive to sample time (see Advanced Application Note 005 “Effect of Sample Time ….”)

If the controller gain is increased or the wireless resolution setting is made finer, the PIDPLUS can provide tighter control. For a loss of communication, the PIDPLUS offers significantly better performance than a wired traditional PID particularly when rate action and actuator feedback (readback) is used


Self-Regulating Process ResponseSelf-Regulating Process Response

pf Lambda (closed loop time constant) is defined in terms of a Lambda factor (f):

Most continuous processes have a self-regulating response (PV lines out in manual)

Closed loop time constantfor setpoint change

Response to change in controller output with controller in manual

Time (seconds)

% Controlled Variable (CV) or

% Controller Output (CO)

CO

CV

op

Kp = CV CO

CO

CV

self-regulating process time constant

Self-regulating process gain (%/%)

observed process

deadtime

CV


Integrating Process ResponseIntegrating Process Response

Lambda (closed loop arrest time) is defined in terms of a Lambda factor (f):

if K/

Most batch processes have an integrating response (PV ramps in manual)

observed process

deadtime

Time (seconds)o

Ki = { [ CV2 t2 ] CV1 t1 ] } CO

CO

ramp rate isCV1 t1

ramp rate isCV2 t2

CO

CV

Integrating process gain (%/sec/%)

Response to change in controller output with controller in manual% Controlled Variable (CV) or


Closed loop arrest timefor load disturbance


Exothermic reactors, strong acid-base pH systems, and compressor surge can exhibit a runaway response (PV accelerates in manual)

Runaway Process ResponseRunaway Process ResponseRunaway Process ResponseRunaway Process ResponseResponse to change in controller output with controller in manual

p p’

Noise Band

Acceleration

CV

CO

CV

Kp = CV CO Runaway process gain (%/%)

% Controlled Variable (CV) or


Time (seconds)observed process

deadtimerunaway process

time constant


Adaptive Control Tuning Adaptive Control Tuning for Integrating Process (Batch Temperature)for Integrating Process (Batch Temperature)

Adaptive Control Tuning Adaptive Control Tuning for Integrating Process (Batch Temperature)for Integrating Process (Batch Temperature)


Adaptive Control Models Adaptive Control Models for Integrating Process (Batch Temperature)for Integrating Process (Batch Temperature)

Adaptive Control Models Adaptive Control Models for Integrating Process (Batch Temperature)for Integrating Process (Batch Temperature)


Adaptive Control Learning Setup Adaptive Control Learning Setup for Integrating Process (Batch Temperature)for Integrating Process (Batch Temperature)

Adaptive Control Learning Setup Adaptive Control Learning Setup for Integrating Process (Batch Temperature)for Integrating Process (Batch Temperature)


Adaptive ControlAdaptive ControlGain 40 Reset Gain 40 Reset 500500Adaptive ControlAdaptive ControlGain 40 Reset Gain 40 Reset 500500

Output comes off high limit at 36.8 oC

0.30 oC overshoot


Adaptive ControlAdaptive ControlGain 40 Reset Gain 40 Reset 50005000Adaptive ControlAdaptive Control

Gain 40 Reset Gain 40 Reset 50005000

Output comes off high limit at 35.9 oC

0.12 oC overshoot

Zero overshoot found to occur for Gain = 66 and Reset = 5000


Integrating and Runaway Process TuningIntegrating and Runaway Process TuningIntegrating and Runaway Process TuningIntegrating and Runaway Process Tuning It is difficult to prevent overshoot in processes without self-regulation Controller gain adds self-regulation via closed loop response Examples of integrating processes (ramping response) are

– Liquid and solids level – furnace, column, or vessel pressure – batch composition, pH, or temperature

Examples of runaway processes (accelerating response) are – exothermic reactor temperature– strong acid - strong base pH– compressor speed during surge

An overdrive of the controller output beyond its resting value is needed to reach a set point or compensate for a disturbance (achieved by high controller gain)

The maximum allowable controller gain for many integrating processes is well beyond the comfort level of most users. Measurement noise and resolution often sets the practical high limit to the controller gain rather than process dynamics

Too much reset action (too small of a reset time) causes severe overshoot A higher controller gain creates more overdrive for small setpoint changes and gets

controller off it’s output limit sooner for large setpoint changes There is a window of allowable controller gains.

– Instability from too high of a controller gain (not likely for industrial processes)– Slow rolling oscillations from too low of a controller gain (common case) that slowly decay

for integrating processes but can grow for runaway processes till it hits physical limits


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Where To Get More InformationWhere To Get More Information Where To Get More InformationWhere To Get More Information MYNAH Website – www.mynah.com

– DeltaV Operator Training Systems with MiMiC

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– MYNAH YouTube Series Martin Berutti, MYNAH Technologies

[email protected], +1.636.681.1567Skype: mberutti

Slide 1 Exceptional Process Control Opportunities - Smart and Wireless Instrumentation, Valves, PID,...

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