To investigate the model and control for the boiler- and ...due to inbuilt ON-OFF control for...

School of Engineering and Information Technology

To investigate the model and control for

the boiler- and steam-heated coil systems

A thesis submitted to the School of Engineering and Information Technology, Murdoch

University in partial fulfillment of the requirements for the degree of

Bachelor of Engineering Honours [BE(Hons)]

Instrumentation and Control Engineering

Industrial Computer Systems Engineering

Nur Mazliyana Osman

Supervisor: Associate Professor Graeme Cole

January 2018

ii

Declaration

I, Nur Mazliyana Osman declare that this thesis report is my work, except for the referenced material

which has been acknowledged in the Bibliography.

………………………………………………………

Nur Mazliyana Osman

iii

Abstract The boiler is part of an essential system in process control and instrumentation that requires precise

control to maintain its efficiency. Based on previous works, the boiler system in Instrumentation

Control Engineering (ICE) laboratory was reported as being unable to fully support the steam demand

for the heating purpose in the steam-heated coil system. The causes of this problem were not

explained. In this thesis project, further investigation was conducted to find the causes. The report

will start with a brief introduction about project background, chronology of previous works and

project objectives. The project background will address the steam demand problem and why it can

affect the heating process in the steam-heated coil system. There are three objectives highlighted in

this thesis. One of the objective to control the temperature of the outlet water from steam-heated

coil system. The following section provides a more in-depth about the control strategies and

instrument used in boiler- and steam-heated coil systems. Two control strategies will be presented

within this thesis, which is Proportional Integral (PI) and cascade control to control the temperature of

the outlet water from steam-heated coil system. Following this, calibration was undertaken on

instruments to establish their reliability for data collection. Open loop testing on the steam-heated

coil system is carried to find the best model for better controllability. This test also proves the steam

supply from boiler unable to support the heating process for steam-heated coil system. It concluded

that the pressure of the steam supply is the disturbance variable in steam-heated coil system. A

detailed analysis on the pressure behaviour of steam supply form the boiler system is conducted to

find the causes of the steam demand problem. The boiler system produces an ON and OFF pattern

due to inbuilt ON-OFF control for controlling water level inside the drum boiler in the system.

Furthermore, this pattern shows that the boiler system has a nonlinear behavior that requires an

extreme understanding in the modeling phase. Then, a simplified model and dynamics model were

created for the boiler- and steam-heated coil systems by using two methods, which are an

experimental and theoretical method. These models are used to aid in the controller tunning process.

Only the steam-heated coil system was allowed to have a controller implementation. Two different

tuning methods were used for finding PI controller parameter, which were relay and Ziegler - Nichols

stability margin tunings. Then, both models are tested out for accuracy before used for tuning phase.

A few recommendations for improvement in boiler system were listed in future works section.

iv

Acknowledgments

I would like to express my sincere gratitude to Associate Professor Graeme Cole and Dr. Lihn Vu for

their supervision and efforts during this thesis project. Many of the ideas in this thesis are from

discussion with both.

A note of thanks is extended to Mr. Lafeta Laava and Mr. Graham Malzer for technical assistance in

this project. I also would to thanks to everyone who have helped and supported into making this

thesis project possible.

Lastly, I dedicate my thanks to my family and Noor Amnani Ahmad for their nonstop support and

encouragement they have given to me.

Nomenclature

Symbol Unit Description

A 𝑚2 Area

ℎ J/kg Specific enthalpy

𝐶𝑝 J/kg K Material-specific heat capacity

P Pascal Pressure

Watt Flow rate of heat

𝜌 kg/ 𝑚3 Density

q kg/s Flow rate of mass

V 𝑚3 Volume

𝑉0 𝑚3 Volume in hypothetical situation

𝑙 mm Drum water level

𝜏𝑑 s Residence time of steam in drum

i

Abbreviations

Abbreviations Description

CSHT Continuous stirred heating tank

PI Proportional integral

LabVIEW Laboratory virtual instrument engineering workbench

ICE Instrumentation and Control Engineering

DPT Differential pressure transmitter

inH2O Inch water

Cv Discharge coefficient

RTD Resistance Temperature Detector

PV Process variable

MV Manipulated variable

SP Set point

PDCSO Property, Development and Commercial Services Office

ii

Table of Contents 1. Introduction ............................................................................................................................. 1

1.1. Project background ................................................................................................................. 1

1.2. Chronology of previous work .................................................................................................. 2

1.3. Project objectives .................................................................................................................... 3

1.4. Organization of thesis .............................................................................................................. 4

2. Process, instruments and control strategies description ...................................................... 5

2.1. National Instrument LabVIEW Platform .................................................................................. 5

2.2. System Identification Toolbox in MATLAB ............................................................................... 5

2.3. Boiler- and Steam-Heated Coil systems................................................................................... 5

2.3.1. Boiler system ................................................................................................................... 7

2.3.2. Steam-heated coil system ............................................................................................. 10

2.4. Instrumentation .................................................................................................................... 11

2.4.1. Steam pressure .............................................................................................................. 11

2.4.2. Control valve ................................................................................................................. 13

2.4.3. Water flow meter .......................................................................................................... 14

2.4.4. Steam Trap .................................................................................................................... 15

2.4.5. Resistance Temperature Detector (RTD) ....................................................................... 16

2.5. Control strategies .................................................................................................................. 17

2.5.1. Variables Measured ....................................................................................................... 20

3. Instrument calibration and testing ....................................................................................... 21

3.1. Control Valve ......................................................................................................................... 21

3.1.1. Control valve opening stroke for cold water application ............................................... 22

3.2. Water flow meter .................................................................................................................. 23

3.2.1. LabVIEW’s program for feedwater flow rate to CSHT measurement ............................ 25

3.3. Resistance Temperature Devices (RTD) ................................................................................. 27

4. Steam-heated coil: empirical process modelling ................................................................. 28

4.1. Model formulation ................................................................................................................ 28

4.2. Step response ........................................................................................................................ 28

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4.3. Development of system model ............................................................................................. 33

5. Boiler system ......................................................................................................................... 37

5.1. Development of experimental model.................................................................................... 37

5.2. Development of theoretical process model .......................................................................... 45

5.2.1. Drum boiler model ........................................................................................................ 47

5.3. Boiler system problems ......................................................................................................... 49

6. Choosing controller parameter ............................................................................................ 50

6.1. PI controller ........................................................................................................................... 50

6.1.1. Controller tuning without process model using relay tuning ........................................ 50

6.1.2. Controller tuning with process model ........................................................................... 54

6.2. Cascade controller ................................................................................................................. 57

7. Summary and future work .................................................................................................... 59

8. References ............................................................................................................................. 61

9. Appendices ............................................................................................................................ 64

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Lists of Figures

Figure 1: Boiler- and steam-heated coil system that available at the Murdoch University ..................... 6

Figure 2: Boiler [6] ................................................................................................................................... 7

Figure 3: Pump that feed in the mixture of raw water with sodium hydroxide ...................................... 9

Figure 4: Schematic diagram of the drum boiler [10] .............................................................................. 9

Figure 5: Steam-heated coil system with CSHT and measurement instrument .................................... 11

Figure 6: Differential Pressure Transmitter and Orifice plate ................................................................ 12

Figure 7: Differential pressure transmitter [14] .................................................................................... 12

Figure 8: Danfoss (MAG3000) flow meter attached to the Research Badger Control Valve ................. 14

Figure 9: Principle of electromagnetic flow meter [13] ......................................................................... 15

Figure 10: Operation of inverted bucket steam trap [21] ..................................................................... 16

Figure 11: RTD construction [23] ........................................................................................................... 16

Figure 12: Block diagram for a simple process ...................................................................................... 17

Figure 13: Cascade control system ........................................................................................................ 19

Figure 14: Steam flow rate response to the control valve changes in 60 seconds ................................ 21

Figure 15: Zero span adjustment box located beside to control valve .................................................. 22

Figure 16: Control valve opening stroke characteristic ......................................................................... 23

Figure 17: The digital vs. manual reading of cold water’s flow rate ...................................................... 24

Figure 18: Relationship between the LabVIEW and digital flow rate readings. ..................................... 26

Figure 19: Implementation of correction equation in the LabVIEW program ....................................... 26

Figure 20: Front panel of open loop test in LabVIEW ............................................................................ 29

Figure 21: Step response when the steam's control valve is stepped to 40% of opening. .................... 30



Figure 24: Step response when the steam's control valve is stepped to 100% of opening. .................. 31

Figure 25: The heating process in CSHT ................................................................................................ 33

Figure 26: Components used in the steam-heated coil system ............................................................. 33

Figure 27: Result from the Identification toolbox in MATLAB for the process model ........................... 34

Figure 28: Block diagram of steam-heated coil system in Simulink ....................................................... 35

Figure 29: Step respond of the process model in Simulink ................................................................... 35

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Figure 30: Step response of each opening in the steam's control valve................................................ 36

Figure 31: Two types of behaviour in the pressure of the incoming steam to CSHT ............................. 38

Figure 32: Initial behaviour of the pressure based on steam's control valve opening .......................... 39

Figure 33: The comparison of the second behaviour ............................................................................ 40

Figure 34: Structure of the P1Z transfer function ................................................................................. 41

Figure 35: The behaviour of pressure without the switch and clipping ................................................ 42

Figure 36: The behaviour of steam supply's pressure with the switch and clipping ............................. 42

Figure 37: Simulink model of the boiler- and steam-heated coil system .............................................. 43

Figure 38: Schematic diagram of drum boiler [10]. ............................................................................... 45

Figure 39: Simulink model of the boiler system .................................................................................... 48

Figure 40: Closed-loop response with the relay controller [27]. ........................................................... 50

Figure 41: Front panel of LabVIEW for relay tuning .............................................................................. 52

Figure 42: Block diagram of LabVIEW for relay tuning .......................................................................... 52

Figure 43: Response to relay controller ................................................................................................. 53

Figure 44: Approximation transfer function .......................................................................................... 54

Figure 45: Comparison between the actual and approximation model ................................................ 55

Figure 46: Comparison of the PI controller without the disturbance effect .......................................... 55

Figure 47: Result of PI controller ........................................................................................................... 56

Figure 48: Cascade controller respond .................................................................................................. 58

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List of Table

Table 1: Boiler's specification .................................................................................................................. 8

Table 2: Metal plate information ........................................................................................................... 13

Table 3: Cv and lift chart [16] ................................................................................................................ 14

Table 4: Comparison between of digital and manual reading of cold water's flow rate ....................... 24

Table 5: LabVIEW flow rate readings against the digital flow rate ........................................................ 25

Table 6: The temperature difference between RTD and digital thermometer readings ....................... 27

Table 7: Average temperature of step response ................................................................................... 32

Table 8: The comparison of the final temperature for the outlet water ............................................... 36

Table 9: Period calculation based on the points and steam's control valve opening ............................ 39

Table 10: Average period of all opening in steam's control valve ......................................................... 40

Table 11: The best fit and parameter values from Identification toolbox in MATLAB ........................... 41

Table 12: Calculated error of the final temperature of the outlet water .............................................. 44

Table 13: Input of the boiler based on the product brochure [6] .......................................................... 48

Table 14: Calculated values based on the relay controller response .................................................... 53

Table 15: Ziegler - Nichols Stability Margin Controller Tuning Parameters [28] .................................... 54

Table 16: Calculated controller's parameter ......................................................................................... 54

Table 17: PI controller parameter ......................................................................................................... 55

Table 18: Cascade parameter ................................................................................................................ 57

1

Chapter 1

1. Introduction

This thesis investigates the suitable model and controller for the steam-heated coil systems by

considering:

i. The pressure of steam supply from the boiler system as a disturbance variable.

ii. Heat up water in the steam-heated coil act as the process.

Then, the selected controllers in the steam-heated coil system are tested out to see their

capabilities. These control strategies are to control the outlet temperature in the steam-heated

coil system to achieve the third objectives in this thesis project. However, this action is difficult to

implement due to nonlinearity behaviour of heat source, which is the boiler system. Thus, it is

crucial to model the boiler system first. Also, it also found out that the boiler system used for this

thesis was unable to meet the steam demand to heat water in the steam-heated coil system. This

problem was discovered by analysing a previous student’s thesis. Thus an investigation is

conducted on this system to understand and identify the reason in this incapability. The first

chapter of this thesis explains the project background and objectives to develop an

understanding of this thesis.

1.1. Project background

This project uses two systems, which are boiler- and steam-heated coil systems. Steam-heated

coil system is located inside the ICE laboratory while the boiler system is in a room adjacent to ICE

laboratory. The steam-heated coil system uses a submerged coil to heat water in the Continuous

Stirred Heating Tank (CSHT). This coil uses steam produced by boiler system as a source of heat.

Based on the previous thesis [1], the boiler system is unable to meet the required steam demand

for heating as it suddenly shut down the steam supply. This action caused the amount of steam

delivered to the system was inconsistent, and the heating system failed to maintain at the desired

temperature. Further investigation was conducted on the boiler system to find the causes of this

problem. Therefore, a new understanding is needed for this project to help in modeling tasks.

As this problem will affect the heating process in the steam-heated coil system, it can be

concluded that the boiler system is the disturbance of this system. The only measured variable

coming from the boiler system is the pressure of the steam that been supplied to the steam-

heated coil system. Thus, this variable is selected as the disturbance variable for the steam-

heated coil system.

2

The boiler system is investigated by monitoring the steam pressure reading that will associate

with the LabVIEW program. Also, a suitable nonlinear model for the boiler system is selected to

understand its natural behaviour that causes incapability of supply steam demand.

Then, the model of steam-heated coil system will be modelled, as it is used to select the suitable

controller. This project will focus more on the temperature control rather than the level control.

The primary interest is to control and maintain the outlet temperature of the steam-heated coil

system at the desired temperature. Before modeling task for both systems start, calibration is

essential to establish the reliability of the instrument [2].

1.2. Chronology of previous work

This project is based on a previous student’s thesis [1] that encountered a problem in supplying steam

demand to steam-heated coil system. After analyzing the previous thesis, it was found that the study

did not take account of the behavior of boiler system that plays disturbance role to steam-heated coil

system. Below is a list of previous work:

1) Understand the description of the process and instruments

The previous student had done some background research on both systems. However, he is

more focused on the steam-heated coil system instead of the boiler system. LabVIEW

program use as a platform for programming in the project. The boiler system in the current

project already identifies as an electrical boiler manufactured by the Simons Boiler. The

steam-heated coil system is referred to as the Continuous Stirred Heating Tank (CSHT) in the

previous thesis. This system is used to symbolize a process in process control learning and

teaching.

2) Calibrate and test the instrument

All the instruments involved in both systems had been calibrated by using several methods to

establish the reliability of the instrument. The previous student calibrated the instrument

used in the system. Then this calibration curve equation is inserted in LabVIEW program itself.

3) Collect the measurement and calculate the heat transfer in steam application

The previous study collected and measured the condensation of steam to calculate the steam

heat transfer and steam flow rate. Furthermore, the measurement is taken in the calibration

tasks used for calculating the heat transfer in the steam application as well.

3

4) Develop the model and linearize it

The previous study focused on the CSHT and steam valve despite the boiler also play a crucial

role in the heating system. The boiler system has its own behavior that needs to include for

developing a proper controller in steam-heated coil system. Mathematical modeling was used

instead of real data to model the boiler system. Then the model was used to obtain a transfer

function for the process.

5) Controller design and testing

After modeling CSHT and steam valve, the model then was used in the Simulink for tuning.

The previous thesis used the models to design two types of the controller which were

Proportional Integrated (PI) and cascade controller. He used the opening of steam control

valve as the manipulated variable and the water temperature inside the CSHT as the control

variable. Then, the developed controller was tested out by using two methods, which were

set point tracking and disturbance rejection, by using simulation only instead of the

implement on the real systems.

1.3. Project objectives

The project on modeling and controlling the boiler- and steam-heated coil systems has three primary

objectives, which are:

(i) To understand the connection, setup, operation and instrumentation for the whole systems.

Before running the whole system, calibration and checking on the instrumentations are

necessary to establish the reliability of the instrument. Extra instrumentation will be added to

improve the performance of the systems. For example, in the boiler system, an electrical

power measurement is installed to monitor the power of the boiler system.

(ii) To understand in detail quantitatively about the boiler system

Boiler plays a crucial job as it supplies the steam for the steam-heated coil system. A

thorough investigation of the boiler system is needed to identify the reason on incapability of

the heating system to provide sufficient steam demand. This project modelled the boiler

system by using two methods which was an experimental and theoretical method.

4

(iii) To understand and control the steam-heated coil system.

This project considers the boiler system to understand in detail about the steam-heated

system. The interest in this thesis project is to control the temperature at the outlet of the

steam-heated system based on the desired set point. The control strategy will be needed to

achieve this objective.

1.4. Organization of thesis

Chapter 2 is a literature review of this thesis. First, it introduces boiler- and steam-heated coil

systems. Details are focused on the instruments involve in both systems with its fundamental

principle and specifications. Then, it continues with the prediction of a suitable control strategy that

can be implemented through this thesis. Also, process variables measured are listed out for control

purpose.

Chapter 3 explains calibration process that been conducted on the instruments to establish its

reliability. Different instruments have different calibration process. Calibration of the instrument and

LabVIEW program are essential for accurate readings to model both systems.

In chapter 4, experimentation is carried by running both systems simultaneously in open loop. Then,

this chapter will be more focusing on modelling the steam-heated coils system. Mathematical

modeling of the systems is developed using the experimental method and compared with the real-

world system

Chapter 5 is model identification section for the boiler system. This chapter gives an idea regarding

the disturbance behavior, causes, and effect on the heating process. Two methods are used in the

system modelling which are an experimental and theoretical method. Then, it will test out with

process model found in Chapter 4

Chapter 6 is where the implementation of different control strategies. Tuning tasks are essential

before implementing any control strategy to find the best controller parameters. A Proportional

Integrated (PI) and cascade are selected as the control strategies for the steam-heated coil system.

Chapter 7 is the summary and future work of this thesis project. While in chapter 8 is the references

used in to complete this thesis.

5

Chapter 2

2. Process, instruments and control strategies description

A better understanding of both systems is needed before starting the technical tasks. The boiler

system required much information, especially in the basic operation and structure. A basic operation

of each of the instrument is also needed before the calibration tasks. The guidelines are necessary for

the longevity of the instrument. The selection of the control strategy is crucial as it used to achieve

one of the objectives of this project.

2.1. National Instrument LabVIEW Platform

The National Instrument LabVIEW program is a platform for real-time data monitoring and

controls the steam-heated coil system. A LabVIEW is graphical programming that helps to require

data acquisition and control application [3]. This project can have a user interface with controls

and indicators with help from LabVIEW. In the block diagram, all the control algorithms will be

implemented, or users can choose the different types of built-in controller. It also has a data

logging function in Excel file CSV format.

2.2. System Identification Toolbox in MATLAB

The toolbox provides identification techniques for constructing a mathematical model in transfer

function form of dynamics system based on the experimental data [4]. It helps to present a

simplified model of the complex system. The toolbox also provided the graphical of the best fit of

the model compared with the measured data [5].

2.3. Boiler- and Steam-Heated Coil systems

This thesis project uses boiler- and steam-heated coil systems that are used for teaching purposes

in ICE laboratory (see Figure 1). The outlet water’s temperature of the steam-heated system will

be monitored and controlled at the desired temperature.

6

FT01

PT01

TT01

FT02

TT03

TT02

Steam in Control valve 1

Steam trap

CondensateWater out

Control valve 2

Cold water in

Ball valve 6

Continuous Stirred Heating Tank

P

Ball valve 4

Safety valve

Pressure gauge

To drain

Ball valve 3

Pump

Ball valve 2

Ball valve 1

Dosing pump

Sodium Hydroxide tank

Boiler system

Steam heated coil system

Boiler

Figure 1: Boiler- and steam-heated coil system that available at the Murdoch University

7

2.3.1. Boiler system

A boiler is a closed vessel that provides heat energy to convert the water into pressurized steam. This

thesis project uses the same type of boiler as the previous thesis. It identifies as an electrical boiler

manufactured by the Simons Boiler that follows the Australian Standard No.1228 [6]. The boiler

model is SB 2S/60 steam boiler, and the dimensions shown in Figure 2. The manufacturer provides

the boiler specification as shown in Table 1. It locates in a storage room adjacent to the

Instrumentation and Control Engineering (ICE) laboratory by steam pipeline. An electrical boiler uses

electricity rather than fuel or gas to heat the water to its boiling point. This boiler run by using three-

phase, 50 cycle power supply to fulfill high current usage. The electrical power runs through the

heating element within the boiler, which acts as the resistor to produce heat through the resistance.

The flowing current in the heating element turns the electrical energy into thermal energy. The

electrical boiler uses two type heat transfer, which are conduction and convection. The heat is

transferred through the water by conduction since the heating element immersed in the water. Then

the heat is transferred within the water by convection until the water turns to steam. This boiler

system is made up of feed water and heating systems.

Figure 2: Boiler [6]

8

Table 1: Boiler's specification

Boiler Model No. SB 2 s/ 60

Power Input 14 KW

Electrical Supply 20 AMPS

415 VOLTS

3 PHASE

Date of Manufacture 25. 10. 07

Test Pressure 1125 kPa

Design Pressure 750 kPa

Boiler Serial No. S 9003

Date of Shell Cert. 27. 7. 05

The boiler came with several specifications provided by the manufacturer, which shows in

Table 1. For boiler model used in this project, the steam capacity is 18.8 kg/hour at 690 kPa.

It also uses 14 kW to heat up the water inside the drum boiler.

2.3.1.1. Feed water system

The feed water system is to supply water to boiler automatically, depending on the drum

water level inside the steam boiler. It consists of two primary sections, which are the raw

water tank and the pumps. The raw water tank holds raw water straight from the water

source. This system does not use condensed steam or makeup water as a water source. Then

it mixes up with water treatment chemical, sodium hydroxide, to provide a highly alkaline

environment for the boiler. As the temperature increase in the boiler, it will increase the

corrosive rate [7]. Correct alkalinity range which is between 10.5 and 12.0 pH helps to

minimize the corrosive rate in the boiler [8]. The sodium hydroxide is dosing into the tank by

using dose pump to maintain the right alkalinity level and prevent it from corrosion.

An electrical motor-driven pump is used in this boiler system to pump the water from the

raw water tank. The pump mounted to boiler cabinet as shown in Figure 3.

9

Figure 3: Pump that feed in the mixture of raw water with sodium hydroxide

2.3.1.2. Heating system

A drum boiler is a reservoir for water and steam inside the steam boiler. It also separates the

saturated steam and water that makes it a crucial part of the boiler system. A simple

schematic diagram of the drum boiler is shown in Figure 4, which consist of a drum, riser and

downcomer sections. The heat Q is supplied to water at the riser section through the heating

element. This is causing the water to boil and lead to a difference in water densities causing

a circulation in the riser-drum-downcomer loop [9]. Feedwater, 𝑞𝑓 is pumped to drum and

saturated steam, 𝑞𝑠 is taken out from the drum.

Figure 4: Schematic diagram of the drum boiler [10]

10

Then the steam is piped to the ICE room for heating purpose in the steam-heated coil

system. This steam-heated coil system is classified as open loop system because the

condensate water is not pumped back to boiler instead exhausted to the drain [11]. The

presence of the saturated steam below the liquid level in the drum causes the shrink-and-

swell phenomenon [9]. The shrink-and-swell is a phenomenon that causes variations in the

level on the liquid surface in the drum based on the changes in steam demand [12].

The safety valve is mounted on the boiler cabinet that helps to protect the boiler system

from getting over pressurized [13].

2.3.2. Steam-heated coil system

A steam-heated coil system, which can be seen in Figure 5, is located in the ICE laboratory is used

for learning purpose. It uses a submerged steam coil in the tank to provide a heat transfer

between the steam and water. This system uses for the heating purpose inside the CSHT. Cold

water is added to the CSHT as the feed water, and then it will be heated using a steam-heated coil

in the CSHT. Here, the steam is transferring the heat energy to water as it utilizes the latent heat

of steam when it condenses. This system has a propeller agitator that used to increase the heat

transfer rate in the water.

The heated water then will be stored in the hot water reservoir that can be used for supply hot

water to other stations. This heated water will be measured to ensure the temperature of the

outlet water is matching with the desired temperature. The amount of the steam flow in the

steam-heated coil system will be controlled by the control valve 1 with the associated signal from

the controller or can be operated manually by the operators. The outlet of the heated steam

system will go back to steam recovery by going through the steam trap.

11

Figure 5: Steam-heated coil system with CSHT and measurement instrument

2.4. Instrumentation

There are three types of measuring devices used in this project, which are for temperature, pressure

and flow rate. The primary purpose of the measuring devices is to measure and convert the physical

signal into electrical signal.

2.4.1. Steam pressure

A steam pressure meter contains two parts that are primary and secondary devices. The

primary device is an orifice plate, sandwiched between two pipe flanges of Differential

Pressure Transmitter (DPT) as shown in Figure 6 to create a difference in pressure as the flow

increase. The secondary device is Differential Pressure Transmitter (DPT) as it uses to

measure pressure difference caused by the primary device.

12

Figure 6: Differential Pressure Transmitter and Orifice plate

A differential pressure transmitter uses to measure the steam pressure through the pipe by

sensing a pressure difference in two ports. It fitted with a mechanical device, which is a

diaphragm that acts as pressure sensing element. The diaphragm deflected depends on the

applied pressure and converted into an electrical signal by using strain gauge. It has two-

pressure ports label as “High” and “Low.” The “+” and “-” symbols do not imply the polarity

of the input voltage. These symbols represent the different effects on the diaphragm that is

clarified in Figure 7.

Figure 7: Differential pressure transmitter [14]

This project uses an electronic differential pressure transmitter from Rosemount

1161DP5S22B117, which can identify by its physical appearance. The electronics type is

indicated by the blue cover in the top half that contains wires. The output signal from the

13

differential pressure transmitter is 4-20mA. It has transmitter range availability up to 750

inH2O that equivalent to 186.4 kPa [15].

2.4.2. Control valve

There are two control valves used in this project, which is for steam and water application.

Both control valves are from Research control valve, low-flow control type 807. The valves

are pneumatically operated globe control valve with a range of operating pressure up to

5,000 psi [16]. The steam control valve is used to control the amount of steam needed to

heat up the water in the steam-heated coil system. While for water control valve is used to

control the flow rate of water into the steam-heated coil system. Based on the metal plate

located on the top red housing as shown in

Table 3, these valves are trim size C which it has a range of a discharge coefficient (Cv) is

between 0 for minimum and 1.25 for the maximum as highlighted in Table 4. At maximum

Cv, the pressure drop in steam supply will be around 15 inH2O which can be seen in

Appendix A.

Table 2: Metal plate information

ACT AT0

SIG 3 – 15

TRIM C

SERIAL NO. Steam control valve 232160

Water control valve 232163

MOD NO 1002GCN36SV0SCLN36

14

Table 3: Cv and lift chart [16]

These control valves consist of actuator, valve, and positioner. The Badger meter valve

positioner moves the piston of the pneumatic actuator to a corresponding position based on

the signal from the controller and holds that position.

2.4.3. Water flow meter

A Danfoss (MAG 3000) water flow with serial number 083F4001 is an electromagnetic flow

meter. It attached to the control valve for water application, as shown in Figure 8 and used

to measure the water flow rate.

Figure 8: Danfoss (MAG3000) flow meter attached to the Research Badger Control Valve

An electromagnetic flow meter uses Faraday’s Law of induction. The principle of the law is

when a conductive fluid flows through a magnetic field, it generates an electromotive force

15

(voltage) which is proportional to the average flow velocity, pipe diameter and magnetic field

strength [17].

Inside an electromagnetic flow meter, represented in Figure 9, a current is applied to the

exciting coil to generate a magnetic field. When the water flows through the pipe, it induces

a voltage, which is proportional to average flow velocity. Then the sensing electrodes located

at the flow meter body captured this voltage signal and sent to the transmitter for

calculating the volumetric flow rate based on the pipe inner diameter [18].

Figure 9: Principle of electromagnetic flow meter [13]

2.4.4. Steam Trap

A steam trap is an automatic drain valve that filters out the condensed steam, air and carbon

dioxide (𝐶𝑂2) to maintain the operating efficiency of the heating process. Initially, the steam

produced by the boiler system contains heat energy that is used to heat up the water. When

it underwent the heating process, it losses the heat energy and formed a condensate. If the

condensate is not removed immediately, it can slow down the heat transfer in the steam-

heated coil system. Also, the condensate can cause physical damage because of the

corrosion or water hammer [19]. The water hammers occur as the velocity of the

condensate causes ripples in the water until it forms a slug. This slug of condensate capable

to travel at speed of steam and strikes the valve of fitting with a force comparable to a

hammer blow [20].

Inverted bucket trap is a type of the steam trap use in this thesis project. Inverted bucket

trap uses an inverted bucket attached to a lever to a valve. It responds directly to the density

difference between the steam and condensate.

16

Figure 10: Operation of inverted bucket steam trap [21]

The inverted bucket steam trap, represented in Figure 10 with three sequences of operation

inside it. In (i) the bucket sinks when the volume of condensate exceeds 2/3 of the volume of

the bucket. The lever will open the valve that located at the top of the trap. When the

condensate fills up the bucket, it will flow to the bottom of the bucket to fill the trap body.

Then, the condensate water is discharged through the outlet. In (ii) the steam enters through

the inlet, and eventually, the steam volume exceeds 2/3 of the bucket volume. It causes the

bucket to become buoyant, it then rises and closes the valve. In (iii) air and 𝐶𝑂2 pass through

the bleed hole at the top of the trap. The bucket losses its buoyancy as the steam traps

inside the bucket condenses due to radiation process [22]. Then, the bucket will sink and

open up the valve, and the cycle repeats back like in (ii) [21].

2.4.5. Resistance Temperature Detector (RTD)

A resistance temperature detector is a temperature-sensing device by measuring the output

resistance. As the temperature of the water increase, the resistance measured in ohms (Ω)

also increases. All the RTD in this project used Platinum as sensing element, and they are

known as a two-wire system.

Figure 11: RTD construction [23]

17

The RTD used in this project has a similar cross-section with Figure 11. The connecting head

is the housing for the transmitter. The sensing element located inside the protecting tube

that will be immersed in the water. The RTD’s fitting help it to mount on the pipeline. The

transmitter’s signal starts at 4mA for the lowest temperature and increases to 20mA for the

highest temperature. The temperature is measured in degree Celsius (°C). Three RTD were

used in this thesis project to measure the temperature of cold water in, hot water out and

condensate.

2.5. Control strategies

In a simple control system which can be referred to Figure 12, a measured output which usually refers

to a process variable (PV) is measured using the measurement device and compared with the set

point value (SP). The calculated value obtains the deviation as an error signal. Then, the error signal

feed into the controller is used to obtain the manipulated variable (MV). The MV is implemented in

the process to achieve stable control.

Figure 12: Block diagram for a simple process

There are a few control strategies that can be used in both systems depending on the purpose of the

controller itself. For the steam-heated coil system, Proportional Integral (PI) and cascade controller

are selected due to time restriction and their simplicity to implement in the real system compared to

other advanced controllers. PI controller is chosen instead of PID controller because D term can

amplify the noise in the steam-heated coil system which might worsen the effect of the disturbance.

These controllers are tested to see their capabilities to compensate the effect of disturbance in the

heating process. Meanwhile, for the boiler, it was found that this system has a built-relay controller

that is based on the level in the drum boiler. These three control strategies are further explained as

below:

18

a) Proportional Integral (PI) controller for steam-heated coil system

PI uses two basics control action which is the proportional and integral controller.

Proportional (P) factor produces the control output signal from controller proportional to the

current error, ε(t). The proportional gain (Kc) multiplied by the error value will determine the

control output. P factor still has a steady state error, which an error between the set point

and the actual process variable. However, if Kc value is higher than its normal range, the

system will be unstable as the process variables start to oscillate. Integral (I) factor is used to

reduce this steady-state error of the system. It integrates the error term until the error is

eliminated over a period. The downside to the integral factor is the actual process variable

may have an overshoot. Both Kc and integral time will be determined by tuning that will be

discussed in Chapter 6.

b) Cascade controller for steam-heated coil system

A cascade control has two controllers that are a primary (outer) and secondary (inner)

controller as shown in Figure 13. The primary controller is the temperature controller, and the

secondary controller is the pressure controller. In single-loop control, a pressure drop in the

steam supply will affect the temperature of the water before the temperature sensor could

notice it. The cascade controller is used to achieve fast rejection of disturbance over single-

loop control. It is able to provide faster compensation when steam pressure is disturbed. The

presence of the secondary controller, will help to quickly measured and maintained the steam

pressure by comparing the pressure measurement and primary controller output.

19

Figure 13: Cascade control system

The primary controller is used to control the temperature of the outlet water. The primary will try

to regulate the heating process in CSHT by producing a steam pressure set point for the

secondary controller. Then, the secondary controller will try to manipulate the steam’s control

valve opening until the steam is sufficient to heat the water in CSHT. If the temperature of the

outlet water is still below or higher than the desired temperature, the primary controller will

continuously produce a new set point for the second controller. In the cascade control system,

the inner loop must respond faster than outer loop [24].

c) ON-OFF controller for the boiler system

An ON-OFF controller is the simplest control in the feedback control [25]. The controller

drives the MV by using two state which is fully open or fully closed depending on the PV’s

reading to the set point.

20

2.5.1. Variables Measured

Following is a list of the measured variables that are available in both systems:

1) The flow rate of inlet water to CSHT

2) The pressure of steam supply to CSHT

3) The temperature of inlet water temperature to CSHT

4) The temperature of outlet water temperature from CSHT

5) The temperature of condensate

21

Chapter 3

3. Instrument calibration and testing

Instrument calibration is a crucial step before data collection started. This process used to maintain

instrument accuracy and establish the reliability of the instrument [2]. Although different instruments

have a different method of calibration, the calibration process is defined the process of setting up an

instrument to produce data within an acceptable range [26]. All the instruments involved in both

systems had been calibrating by categorizing it into two different section that was, first on the

instruments and then the LabVIEW’s program itself.

3.1. Control Valve

Control valve for the steam application used zero span adjustment for calibration. This method used

to set the range of measurement by adjusting both zero and span. Before the calibration, even

though a zero percent of valve opening was manually inserted into the control valve, the steam’s flow

rate kept showing a reading of more than zero inH2O, which can be seen Figure 14 below. The blue

line indicates the flow rate of steam before calibration while the red line is for the flow rate of steam

after calibration.

Figure 14: Steam flow rate response to the control valve changes in 60 seconds

-5

0

5

10

15

20

25

0 10 20 30 40 50 60

Pre

ssu

re (

inH

20

)

Time (s)

Steam pressure response to control valve changes

Steam flow rate beforecalibration

Steam flow rate after calibration

CV steam in

22

By screwing in an anticlockwise direction at the zero point at grey box beside the control valve as

shown in Figure 15, it adjusts the steam’s flow rate to the constant value of 0.59 inH2O for an output

of 4mA. However, this control valve is not sensitive enough because it not fully close when receiving

4mA signal. While for span adjustment, there is no calibration process been implement as the control

valve received 100 percent, it shows its maximum value of 105inH2O for an output of 20 mA.

Figure 15: Zero span adjustment box located beside to control valve

In the feed water to CSHT application, no calibration needed for the control valve. The valve opening

at zero percent produces 0.001 l/min of cold water’s flow rate while at 100 percent it indicates

around 3.7 to 3.8 l/min.

3.1.1. Control valve opening stroke for cold water application

The control valve received a signal from the control panel of the LabVIEW’s program which has a

signal which ranges between 4 and 20 mA, depending on the valve stroke. The valve stroke is in

percentage value. First, the signal at 20 percent is injected to control valve for cold water application

and then the measurement of feed water flow rate to CSHT was recorded when it reaches its steady

state. The movement of the stroke was checked physically by measuring the indicator scale located

near with the travel indicator at the control valve’s yoke. This process then repeated by injected

continuously to 40%, 60%, 80% and 100% as each different stroke gives different readings as shown in

Figure 16.

23

Figure 16: Control valve opening stroke characteristic

Figure 16 shows two different type of control valve’s stroke which is the blue line is when the control

valve travel upward while the red line is indicating the control valve travel downward.

3.2. Water flow meter

For calibration in the Danfoss (MAG 3000) water flow, the control valve opening in percentage was

changed at uniform intervals between zero and 100 percent. The digital measurement of the flow

rate at Danfoss (MAG 3000)’s screen indicator was recorded to compare with manual measurement.

The cold water flow rate was manually measured using a measuring cylinder and stopwatch to

calculate the volumetric flow rate. Then both measurements were compared as seen in Table 4 to

ensure the accuracy of Danfoss (MAG 3000) measurement.

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

0 20 40 60 80 100 120

Flo

w r

ate

(l/m

in)

Valve opening (%)

Control valve opening stroke for feed water to CSHT

valve up flowrate (l/min)

valve down flowrate (l/min)

24

Table 4: Comparison between of digital and manual reading of cold water's flow rate

Digital flow meter reading

(l/min)

Manual flow meter

reading (l/min)

0.000001 0

1.565 1.995

2.684 3.38

3.506 4.405

4.319 5.653

4.84 6.14

Figure 17: The digital vs. manual reading of cold water’s flow rate

A regression analysis of Figure 17 shows that the equation of the best-fit line is 𝑦 = 1.2822𝑥 −

0.0191 with 𝑅2 = 0.999 which is almost one. This analysis proves that the feed water flow rate to

CSHT measured by the Danfoss (MAG 3000) is reliable for data collection.

0

1.995

3.38

4.405

5.6536.14

y = 1.2822x - 0.0191R² = 0.999

-1

0

1

2

3

4

5

6

7

0 1 2 3 4 5 6

Dig

ital

Met

er r

ead

ing

(l/m

in)

Manual Flow reading (l/min)

flow meter reading calibration (l/min)

25

3.2.1. LabVIEW’s program for feedwater flow rate to CSHT measurement

After flow meter calibration, a LabVIEW’s program needs to be built for recording the data collection.

Small steps of valve opening on the control valve were introduced, then when the flow rate reaches

its steady state, digital readings Danfoss (MAG 3000) flow meter and LabVIEW readings flow were

recorded to compare its value as tabulated in Table 5. The graph in Figure 18 shows the relationship

between the LabVIEW and digital flow rate readings of feed water to CSHT.

Table 5: LabVIEW flow rate readings against the digital flow rate

Digital Danfoss (MAG 3000) flow

meter reading (l/min)

LabVIEW flow rate reading

(l/min)

0.000001 0.04375

0.4978 2.3125

0.8845 4.425

1.289 6.3875

1.63 8.225

2.166 10.7682

2.41 12.1312

2.722 13.7812

3.039 15.3625

3.295 16.4125

3.796 19.1188

4.096 20.4313

4.421 22.3375

4.677 23.275

4.879 24.05

4.93 24.703

26

Figure 18: Relationship between the LabVIEW and digital flow rate readings.

In Figure 18, it shows an equation which was used to find the correction equation for the LabVIEW

program to produce flow rate readings matching with the digital Danfoss (MAG 3000) readings.

Equation 1 is a correction equation after arranging the equation in Figure 19; then it has been

implemented in the LabVIEW program for cold water’s flow rate section as highlighted in a green box

in Figure 19 below.

Equation 1: Equation that used to correct the flow rate reading in LabVIEW’s program

Figure 19: Implementation of correction equation in the LabVIEW program

y = 4.998x + 0.012

0

5

10

15

20

25

30

0 1 2 3 4 5 6

Lab

VIE

W f

low

rat

e re

adin

g (l

/min

)

digital flow meter reading (l/min)

LabVIEW flow rate reading

27

3.3. Resistance Temperature Devices (RTD)

A digital thermometer was used to verify the reliability of the RTD. Three RTD were used in the steam-

heated coil tank, and all of them undergo this test. The first test was at cold water inlet which the

steam was shut off to avoid heating process while the flow rate of the cold water remained same

around 3.5 l/min. Then, the temperature of cold water in was recorded with RTD and digital

thermometer readings simultaneously. The second test was at hot water outlet. The control valve for

steam application was 50 percent opened to heat up the water. After 30 minutes, the temperature of

hot water outlet was recorded with RTD and digital thermometer simultaneously. The last test was at

the condensate stream by using the same setup for recording the temperature of the hot water

outlet. All the data was recorded in Table 6.

Table 6: The temperature difference between RTD and digital thermometer readings

Readings error in the cold water inlet‘s temperature is between 0.06 to 0.08 which indicates that the

RTD is reliable for data collection.

RTD temperature

readings (⁰C)

Digital thermometer

temperature readings (⁰C)

Difference in

temperature (⁰C)

cold water

inlet

17.44 17.37 0.07

17.65 17.58 0.07

17.44 17.36 0.08

hot water

outlet

40.16 40.08 0.08

40.34 40.26 0.08

40.30 40.23 0.07

condensate

41.20 41.14 0.06

41.17 41.10 0.07

41.20 41.14 0.06

28

Chapter 4

4. Steam-heated coil: empirical process modelling

Empirical process modelling requires an experimental data for the model development which

provided by implementing an open loop testing. Open loop test is a test used to run both systems

without implementing a controller to observe the effect of the input variables on the output variables

of the process. The changes of input variable help to provide information about the behaviour of the

process and disturbance based on the observed process response. Then the process can be

characterized for control system design.

4.1. Model formulation

The model formulation in empirical modeling is based on experimental data by using open loop

testing. Therefore, it is essential to collect as much data in the suitable range of operating conditions.

4.1.1. Selection of variables

Based on the third objective, the outlet temperature of the steam-heated system is selected as a

process variable (PV) where it needs to be maintained at the desired temperature. There are two

potential manipulated variables (MV) for the steam-heated coil system to maintain the PV according

to the set point, which are the opening of the control valve for the inlet water and steam to CSHT. The

opening of control valves will create a change in flow rate of feed water and steam supply’s pressure

to CSHT. It is more critical to manipulate the opening of the control valve for steam rather than the

opening of the control valve of inlet water. This selection is made because the opening of the control

valve for the steam supply helps regulate the temperature of the outlet water to its maximum

temperature. Furthermore, this selection also helps to understand the effect of steam supply’s

pressure from the boiler system on the steam-heated coil system. Therefore, it can be concluded that

the fixed parameter for the steam-heated coil system is the opening of feed water’s control valve to

CSHT.

4.2. Step response

Figure 20 shows a simple LabVIEW program is built to control and monitor the step responses.

29

Figure 20: Front panel of open loop test in LabVIEW

It finds that when steam’s control valve was tested on position 20%, steam started to leak out around

an orifice plate in the steam pipeline. Maintenance has been done several of time to fix the leakage,

but unfortunately, it was a failure. It has then been decided to skip 20% of opening on the steam’s

control valve on the open loop test due to time constraints.

The open loop test is used a constant value of 50% for the opening of the water’s control valve that

resulted in an average flow rate of 3.2 l/min for the feed water with an average temperature of

23.9°C. Then, the control valve of steam supply to CSHT is stepped to 40%, 60%, 80% and 100% from

0 %. The step responses are recorded for 80 minutes as shown in Figure 21 until Figure 24.

30

Figure 21: Step response when the steam's control valve is stepped to 40% of opening.


-20

0

20

40

60

80

100

120

0 1000 2000 3000 4000 5000 6000 7000 8000

Val

ve o

pen

ing

(%),

Flo

w r

ate

(l/m

in),

Pre

ssu

re (

inH

20

),

Tem

per

atu

re (

°C)

Time (s)

Step respond when the steam's CV is stepped to 40%

Flow rate of inlet water (l/min) Temperature of inlet water (⁰C)

Pressure of incoming steam (inH2O) Temperature of outlet water (⁰C)

Temperature of the condensate (⁰C) Opening of water's control valve (%)

Opening of steam's control valve (%)

-20

0

20

40

60

80

100

120

0 1000 2000 3000 4000 5000 6000 7000 8000

Val

ve o

pen

ing

(%),

Flo

w r

ate

(l/m

in),

Pre

ssu

re (

inH

20

),

Tem

per

atu

re (

°C)

Time (s)






31



-20

0

20

40

60

80

100

120

0 1000 2000 3000 4000 5000 6000 7000 8000

Val

ve o

pen

ing

(%),

Flo

w r

ate

(l/m

in),

Pre

ssu

re (

inH

2O

),

Tem

per

atu

re (

°C)

Time (s)






-20

0

20

40

60

80

100

120

0 1000 2000 3000 4000 5000 6000 7000 8000

Val

ve o

pen

ing

(%),

Flo

w r

ate

(l/m

in),

Pre

ssu

re (

inH

2O

),

Tem

per

atu

re (

°C)

Time (s)






32

Based on Figure 21 until Figure 24, the most significant response can be seen in the pattern of the

pressure of incoming steam to CSHT that indicates by grey color. This pressure has ON and OFF states

which have resulted in an oscillation in the temperature of the outlet water from CSHT. The ON and

OFF pattern in the pressure of incoming steam to CSHT is produced by the boiler’s pump operation

that received a signal from a built-in ON-OFF controller in the boiler system. This ON-OFF controller

will be explained more in Chapter 5. In the OFF state, the pump will turn on to feed the water into the

boiler system; physically observe in the boiler room as the pump will produce a sound when turns on.

Also, the response of the pressure shows they are clipped at 105.2 inH2O when the steam’s control

valve is stepped up to 80% and 100%. No further investigation is conducted on this clipping issue due

to restriction from Property, Development and Commercial Services Office (PDCSO) of Murdoch

University.

Table 7: Average temperature of step response

Opening the steam's

control valve (%)

Average of temperature (°C)

ON state OFF state

40 56.46 41.25

60 57.90 42.26

80 58.06 42.43

100 58.51 42.62

Table 7 shows the average temperature of the step response when the steam’s control valve is

stepped to 40%, 60%, 80% and 100%. This average temperature is used to select a range for set point

temperature of the outlet water from CSHT. The average temperature was categorized into two

states, on state and off state, and these states were affected by the pattern of the pressure of the

incoming steam. The average temperature in both states is gradually increased, as the opening of the

steam’s control valve is increased. One of the objectives is to control the outlet temperature at the

desired temperature (set-point). The range of set point chosen is between 35⁰C to 52⁰C, which is 6⁰C

to 7⁰C below the average temperature of ON and OFF state for all openings in steam’s control valve.

Also, this range is chosen to reduce an error in the outlet temperature, as it tends to oscillate due to

the pressure incoming steam behavior. This ON and OFF pattern is the reason on why the boiler

system is labeled as the disturbance in the steam-heated coil system as illustrated in Figure 25. A

further investigation on the pattern of the pressure incoming steam will be discussed more detailed in

Chapter 5.

33

Figure 25: The heating process in CSHT

4.3. Development of system model

Steam-heated coil system has three components which are steam’s control valve, water’s control

valve, and process heating components as illustrated in Figure 26. Each component needs its model

to be simulated in Simulink. The steam’s control valve component will be discussed in Chapter 5. In

this section, experimental method is used rather than theoretical method. The theoretical method

uses a mass and energy balance around the system to produce a dynamic model. However, this mass

and energy balance requires some information from additional sensors, for example, the temperature

of steam supply and flow rate of outlet water from CSHT. These additional sensors need to be

installed in the system which is quite costed. This is the reason why the experimental method is

chosen for modelling the system.

Figure 26: Components used in the steam-heated coil system

34

The initial temperature inside the steam-heated coil tank depends on the seasons, which in the

winter; the temperature is around 17⁰C. While in the spring and summer is around 21.5⁰C. As the

water control is stepped to a constant 50% of opening, the temperature inside the tank will be around

23.9⁰C. 23.9⁰C is used as the initial temperature for the water at inlet and inside the CSHT.

Data from open loop test is used to find the best fit in the Identification toolbox for the process

model. This data is recorded before the pressure drop occurs in steam supply that affecting the

heating process in CSHT, which can be refer in appendix A. Each the step response is exported to

MATLAB one by one. The steam’s control valve is selected as MV, and the temperature of the outlet

water is the PV. After testing all the results, it found that the best match for the process model is

when the steam’s control valve is stepped to 80% of opening. It gives almost similar result to the

experimental open loop test for all steam’s control valve opening.

Figure 27: Result from the Identification toolbox in MATLAB for the process model

The best fit is the comparison between the experimental measured temperatures with the model

temperature. Figure 27 shows the best fit is 98.38%, which the process model was assumed to yield

closer approximation to the real heating process before the effect of ON and OFF from disturbance

variable. The heating process in CSHT is assumed linear for easier in modelling purpose. In this case,

the process is affected by a nonlinear behavior of input disturbance which makes it oscillate as shown

in Figure 24 . Then the transfer function in Equation 2 is used in Simulink to represent the process and

compared with real system response.

35

𝐺(𝑠) = 0.361

98.907𝑠 + 1 𝑒−6.368𝑠

Equation 2: Process transfer function equation between MV and PV

A block diagram of steam-heated coil system is built in the Simulink. Initial steady state temperature

inside the tank of 23.9⁰C is added to a result step respond to the process model to produce a 52.78⁰C

of outlet temperature. Before adding the initial steady state temperature, the final temperature of

the outlet of water is 28.85⁰C, this comparison can be referred to Figure 28 and Figure 29 below.

Figure 28: Block diagram of steam-heated coil system in Simulink

Figure 29: Step respond of the process model in Simulink

The steam’s control valve is stepped from zero to 80% at 100s which is indicated by the red line in

Figure 29. The blue line starts at steady state temperature of 23.9⁰C, that based on the constant

temperature when using a 50% of water’s control valve opening.

36

Figure 30: Step response of each opening in the steam's control valve

The process model is tested out at 100s, by stepping out with 40%, 60%, 80% and 100% of the

opening in the steam’s control valve. Figure 30 shows a comparison of each step responds with their

final temperature of the outlet water. The final temperature of the outlet water in simulation has an

error when compared with the experimental that can be seen in Table 8.

Table 8: The comparison of the final temperature for the outlet water

Opening of the steam's

control valve (%)

Final temperature of the outlet water (⁰C)

Experimental Simulation Error

40 56.46 38.34 18.12

60 57.9 45.56 12.34

80 58.06 52.78 5.28

100 58.51 59.98 -1.47

In the experiment, the final temperature produced is almost in the same range which between 56⁰C

to 58⁰C. While in the simulation, the final temperature is increased by 7.21⁰C when the opening of

the steam’s control valve is incremented to 20% for each of the openings. These differences might

result from the built-in ON-OFF controller in the boiler system. To test out the process model found in

this chapter, a development of the boiler system model was performed.

37

Chapter 5

5. Boiler system

There are two methods of modeling the boiler system used in this thesis project. The first method is

by using the step response found in Appendix A that can be called as an experimental method. The

boiler system has a built-in ON-OFF controller which resulted ON and OFF state in the pressure of the

steam supply to the steam-heated coil system as shown in Figure 21 until Figure 24. The ON and OFF

state has a period that needs to be identified to develop the boiler system model. The second method

is a theoretical method which considers all the state variables inside the boiler system. The boiler

system shows a nonlinear behavior that causes the pressure of incoming steam to have a pattern.

After confirming with the Simons Boiler company, the SB 2S/60 steam boiler is fitted with the level

probe. The boiler system has its ON-OFF water level controller that is based on the level probes and

solid state water level control card to control the pump operation. A small amount of current is

passed through the water inside the boiler. This current is detected and amplified by the water level

control card. The signal from the control card is relayed to control the pump. When the drum water is

below the level probe, the control current is broken, and the pump will turn on for a specific period.

When the feedwater fills up the drum up to the level probe, it will restore the control current and

stops the pump. The changes in drum level cause the pressure of the incoming steam to has ON and

OFF pattern. This relation shows the drum level is essential to modeling the boiler system in a

theoretical method.

5.1. Development of experimental model

Based on the step response of the pressure of the incoming steam in Appendix A, there are two

sequences of behaviors. The first behavior is an initial behavior of the pressure after steam’s control

valve has been stepped up. The second behavior is the ON and OFF behavior which occurs after the

first behavior happen. These behaviors are labeled in Figure 31.

38

Figure 31: Two types of behaviour in the pressure of the incoming steam to CSHT

For better analysis, these two behaviours were investigated and illustrated separately. Each initial

behavior of the pressure is illustrated in Figure 32 and the period is calculated. Based on Figure 32 and

Table 9, 100% of the opening has the shortest period compare to the others as it only takes 472

seconds to complete the initial behavior. Both 100% and 80% have an amplitude of 105 inH2O, but

80% takes 1000 seconds to complete the initial behavior. For 60%, and 40% of opening, right after the

steam’s control valve is stepped up, both pressures of the incoming steam are spiking to 105 inH20

before settling down to their constant amplitude. In the 60% of opening, the pressure stays at the

constant pressure of 105 inH20 for 158.5 seconds and then goes down to the constant pressure of 95

inH20. While in 40% of opening, the constant pressure is at 66.8 inH2O and has the longest period to

complete the initial behavior. Based on Table 9, a simple conclusion was made, which is the steam’s

control valve opening is increased, the time to complete the initial behavior will decrease.

39

Figure 32: Initial behaviour of the pressure based on steam's control valve opening

Table 9: Period calculation based on the points and steam's control valve opening

Steam's

control valve

opening (%)

Time (s)

A B C D E F

98 256.5 570 1098 1303.5 1457

100%

472

80%

1000

60%

158.5

1047

1205.5

40%

1359

40

Figure 33: The comparison of the second behaviour

Then the second behavior starts with the off state. Figure 33 shows the second behavior with the

initial behavior is removed. The amplitude of the ON state for both 100% and 80% of the opening is

105 inH20 but has different rising time. For the 40% of opening, the amplitude is 67.7 inH2O and

while in 60% of the opening is 92 inH2O. For all the steam’s control valve opening, they have a similar

period to complete ON and OFF state. Based on Table 10, the total average for one period is 2012.5

seconds. The on state is 79.6% of the total average for one period that equivalent to 1602.3 seconds.

The remaining of 20.4% is the off state which is 410.2 seconds.

Table 10: Average period of all opening in steam's control valve

Steam's control

valve opening

(%)

Average Period

In second In percent

ON OFF

One complete

period ON OFF

40 1600.3 422.8 2023.0 79.1 20.9

60 1619.3 393.0 2012.3 80.5 19.5

80 1620.5 396.3 2016.8 80.4 19.6

100 1569.3 428.8 1998.0 78.5 21.5

Total average 1602.3 410.2 2012.5 79.6 20.4

41

Based on Figure 33, all the on state has an exponential shape, which looks like the first order behavior.

Each of these on states is exported separately to Identification toolbox in MATLAB to find the best-fit

form it. It found that P1Z transfer function is the best fit for all the on state models. The P1Z is a

transfer function with one pole and one zero that has a structure as shown in Figure 34. They have an

average 95% of best fit with the parameter values listed in Table 11.

Figure 34: Structure of the P1Z transfer function

Table 11: The best fit and parameter values from Identification toolbox in MATLAB

Opening in steam's

control valve (%)

Best fit

(%)

Parameter value

Kp Tp1 Tz

100 94.98 1.0549 100.57 3.3032

80 96.35 1.3164 98.188 1.6221

60 95.57 1.548 138.94 31.342

40 93.11 1.6884 179.31 35.451

Average 95.0025 1.401925 129.252 17.92958

Figure 37 shows boiler system is represented in the red dotted box while the steam-heated coil

system is in the blue dotted box. In the Simulink, the initial behavior is removed to avoid complexity

in modeling the boiler, due to all the initial behavior do not have a constant pattern. As the ON and

OFF state has a repetitive pattern, a programmable pulse generator is used to generate it as shown in

Figure 37. This programmable pulse generator is an implemented Simulink block from the MathWorks

[24]. The average value of the ON state and period from Table 10 are fed into the programmable

pulse generator as shown in Figure 37. For simulation purposes, only one disturbance model transfer

function is used to represent all the step respond of the ON state behavior. The switch is used to

represent the real behaviour of pressure in the OFF state as shown in Figure 36. Without the switch in

boiler system model, the pressure does not decrease to zero as shown in Figure 35. The saturation

block is to clip the pressure when it reached more than 105 inH2O.

42

Figure 35: The behaviour of pressure without the switch and clipping

Figure 36: The behaviour of steam supply's pressure with the switch and clipping

This model is tested out by stepping up the steam’s control valve to 40%, 60%, 80% and 100% of

opening at 91 seconds. The first attempt is by using the calculation of the average parameter values

which can be referred to Table 11. Then the second attempt is by trying one by one of the parameter

value of each opening in the steam control valve.

43

Figure 37: Simulink model of the boiler- and steam-heated coil system

44

Then, the comparison was made based on the amplitude of the pressure of incoming steam from both

attempts with the experimental amplitude which can be referred in Appendix C. It was found that when

P1Z’s transfer function of 60% opening has the smallest error for each steam’s control valve opening.

Based on the P1Z’s transfer function of 60% opening in the steam control valve is used as the disturbance

transfer function, the most significant error is found when 40% of the opening is stepped at the steam

control valve, which is the error is 6.105 inH2O that lesser from the experimental value. This error gives an

impact when the output of the P1Z’s transfer function used with the process model found in Chapter 4.

Table 12: Calculated error of the final temperature of the outlet water

Steam's control

valve opening (%)

Final temperature of the outlet water (⁰C)

Experimental Simulation Error

40 56.46 46.27 10.19

60 57.9 57.45 0.45

80 58.06 61.18 -3.75

100 58.5 61.18 -3.31

Error! Reference source not found. shows the calculated error of the final temperature of the outlet water

based ON the OFF state by using P1Z’s transfer function of 60% opening in the steam control valve. When

the steam’s control valve is stepped to 40%, the final temperature dropped to 46.27 ⁰C. As the

experimental method is not very accurate, the theoretical method is considered in modeling the boiler

system.

45

5.2. Development of theoretical process model

In the boiler system, a drum boiler holds a key in modeling the system. Figure 38 shows the working

operation of steam generation in the drum boiler. The drum boiler has two-phase flow and three different

section that related to each other which is drum, downcomer and riser section. These need to be

considered in modeling attempt that makes it complicated. There were a few existing simple physical

models that were found in the existing research papers. Åstöm – Bell model [9] is being selected as a

reference model in this thesis project. The system model is in fourth order nonlinear model. It used mass

and energy balance with an associate of a physical mechanism under a few assumptions [10]. Let the

output produced by the drum boiler be the drum pressure 𝑝, and drum water level 𝑙 [9].

Figure 38: Schematic diagram of drum boiler [10].

To understand the Åstöm – Bell model’s equation, let 𝑉 be a volume, 𝑢 be a specific internal energy, ℎ

specific enthalpy, 𝜌 specific density and 𝑡 temperature. In addition, the subscripts 𝑚, 𝑓, 𝑠, 𝑡 and 𝑤 refer to

the metal, feedwater, steam, total and water [10].

Equation 3 is the mass and global energy balance of the drum in terms of steam flow rate 𝑞𝑠, the

feedwater mass flow rate 𝑞𝑓 and the heat flow rate , which is the inputs of the system. This equation

uses steam tables to find the properties of liquid or vapour mixture to describe the drum pressure

behaviour [10].

46

Equation 3: Mass and global energy balance [10]

The distribution of the steam and water in drum boiler need to take account to obtain a model that can

describe the behavior of the drum water level. In Åstöm – Bell research paper [9], a simple lumped

parameter model is derived to describe the distribution of steam in the riser. This model is represented by

the global mass and energy balance in the riser as shown in Equation 4. The mass fraction 𝛼𝑟 is assumed

linear along the riser [10].

Equation 4: Global mass and energy balance for the riser [10].

Equation 5 and Equation 6 are the empirical models based on a few attempts to fit with the experimental

data by the Åstöm – Bell [10]. Equation 4 is the mass balance of the steam bubbles under the water level in

response to changes in steam flow through the liquid surface 𝑞𝑠𝑑 and the condensation flow 𝑞𝑑𝑐

respectively. The flow 𝑞𝑠𝑑 is driven by the density differences of the mixture (water and steam) and the

momentum of the flow entering the drum 𝑞𝑟 as seen in Equation 6 [9]. Let 𝑉𝑠𝑑0 denotes the bubbles

steam volume at steady state and 𝑇𝑑 denotes the residence time of the steam in the drum [10]. A proper

parameterization of these two terms can capture almost the process dynamic behaviour of flow 𝑞𝑠𝑑 [10].

Equation 5: Mass balance for the steam bubbles under the water level in the drum [10].

Equation 6: Flow rate qsd [10].

47

Before deriving a state model, selection of state variables must be made beforehand. The state variables

should have a good physical interpretation that can describe the accumulation of momentum, mass, and

energy in the drum [9]. The drum pressure describes the total energy 𝑃 and the total mass is represented

by the total water volume 𝑉𝑤𝑡. The distribution of steam and water is captured by the steam quality in the

riser 𝛼𝑟, and the steam bubbles volume under the liquid level 𝑉𝑠𝑑 can be used to estimate the drum water

level. The nonlinear state-space model for this drum boiler will be a 4th order system [10].

The mass and energy balance differential equation is arranged to obtain the differential equations as

shown in Equation 7 [10]. The partial derivatives of the liquid and vapor mixture properties concerning the

pressure are calculated using the coefficient 𝑒𝑖𝑗 which can be refer in Appendix D.

Equation 7: Differential equations in the drum boiler [10].

5.2.1. Drum boiler model

A MATLAB’s script that named as Dboiler is developed to implement the Equation 7 which can be referred

in Appendix E. A user-defined MATLAB function block is used in the Simulink as shown in Error! Reference

source not found. to manage this MATLAB’s script. The inputs for the block are the heat flow into system

𝑄, the steam flow rate 𝑞𝑠, the feedwater flow rate 𝑞𝑓 and drum pressure 𝑃. While the outputs are the

drum pressure and level. The drum pressure is integrated before being fed back as the input.

48

Figure 39: Simulink model of the boiler system

Table 13: Input of the boiler based on the product brochure [6]

Input of the drum boiler

Variable Value

Amount of heat flow rate to the system, 𝑄 14kW

Feedwater flow rate, 𝑞𝑓

Steam flow rate, 𝑞𝑠 18.8 kg/hr

Pressure, 𝑃 690kPa

Water total volume, 𝑉𝑤𝑡 6 liters

Steam quality, 𝛼

Steam bubbles volume under water level, 𝑉𝑠𝑑

Table 13 shows the lists of the inputs used to simulate the boiler system which found in the product

brochure [11]. The grey color indicates that there is no information provided by the brochure. Based on

the developed script in Appendix E, there is a section of the drum boiler parameters and construction data.

This information cannot be obtained due to restriction from The Property, Development and Commercial

Services Office (PDCSO) of Murdoch University and Simons Boiler’s company. A trial and error method

cannot able to produce the outputs based on the step response as the values are different from the real-

world system.

49

5.3. Boiler system problems

The boiler system used in this thesis project has a few technical problems that affect the thesis’s

objectives. The boiler system cannot be dismantled for learning the purpose, as some of the construction

data of the boiler are needed in the theoretical method. The drum, riser, and downcomer need to be

measured for simulation purpose. On 25th until 29th of September, steam was leaking around the

differential pressure transmitter. This problem affected the step response as the pressure keeps changing

when the 20% of opening inserted in steam’s control valve. For safety purpose, the boiler system is shut

down, and the 20% of the opening is removed. On 23th of October until 14th of November, the boiler

system was marked as out service due to the installation of power transducer. Then, as soon the power

transducer was installed, the boiler system started to trip. At first, the problem was solved by flipping back

the switch at the Instrumentation and Control main switchboard (DB). However, it tripped again after 15

minutes of using the boiler system. After thoroughly checked, it found that the boiler system drawing a

significantly higher current on the red phase compare to the rest due to damage to the heating element

inside the boiler. A work request has been submitted to the Property, Development and Commercial

Services Office (PDCSO) to fix the boiler system. This problem has not been solved until this thesis project

finished.

50

Chapter 6

6. Choosing controller parameter

The process of choosing controller parameters is a crucial step to achieve the performance objective.

There are several ways to tune the controller parameter which can be categorized into two group: when

explicit process models are available, and when they are not. This thesis project used two type of controller

which are PI and cascade controllers. Both controllers are chosen due to the time constraints.

6.1. PI controller

In choosing the PI controller parameters, two tuning methods are selected, which are tuning with and

without the process model. Then, these two methods are being compared to select the best control

parameter for achieving the desired temperature.

6.1.1. Controller tuning without process model using relay tuning

The real-world system is used directly to tune when the process model is not available. This method is

taking count the disturbance behavior. A simple relay controller can be used to determine the ultimate

gain (Kcu) and ultimate period (Pu). The relay controller needs a specific amplitude h with constrained

controller action –h ≤ u ≤ h.

Figure 40: Closed-loop response with the relay controller [27].

Figure 40 shows that ultimate period (Pu) is from error output of the period of the closed-loop

response and 2A is the amplitude of the error. Set point minus PV can calculate the error. 2h is the

amplitude of the MV that has upper and lower limit.

51

The ultimate gain is given by:

Equation 8: Relation between the Kcu with h [27].

Where,

h = the control amplitude (MV)

A = resulting output amplitude (error)

This approach requires small changes in PV to find control parameter and does not require entire

process to be brought to the verge of instability. After that, when ultimate gain, Kcu and ultimate

period, Pu is obtained, using Table 15 (Ziegler – Nichols Stability Margin Controller Tuning Parameter)

to find specific values of controller parameters based on controller type. The formula used in the

LabVIEW’s is:

IF (Current PV > Set point + error, MV high, IF (Current PV < Set point-error, MV low, previous MV))

The explanation of the formula is, if the current outlet temperature (PV) is greater than set point plus

error then the steam’s control valve will open based on the MV high. If the current PV is less than set

point minus error, then the steam’s control valve will open based on the MV low else if the all the

requirement does not meet, it will go the previous MV. This formula is implemented in the LabVIEW as

shown in Figure 41 and Figure 42.

52

Figure 41: Front panel of LabVIEW for relay tuning

Figure 42: Block diagram of LabVIEW for relay tuning

Based on Figure 41 and Figure 42, a button was built to change the mode from manual to relay. A set point

and error tabs in Figure 42 helps the user to change the values without stopping the LabVIEW. The set

point value used in the relay tuning is 25°C while the error is ± 5 %.

53

Figure 43: Response to relay controller

Table 14: Calculated values based on the relay controller response

Parameters Value

Pu 789.5

2A 10

A 5

2h 20

h 10

Kcu 2.546479

54

A result is illustrated in Figure 43 shows the response of relay controller. Then, all the parameters are used

to calculate Kcu based on the Equation 8, which can be seen in Table 14. The specific values of proportional

gain (Kc) and integral time (𝜏𝐼) is calculated by using Ziegler – Nichlos Stability Margin Controller Tuning

Parameter which is shown Table 15 and tabulated in Table 16.

Table 15: Ziegler - Nichols Stability Margin Controller Tuning Parameters [28]

Controller Type Kc 𝜏𝐼 𝜏𝐷

P 0.5 Kcu _ _

PI 0.45 Kcu Pu / 1.2 _

PID 0.6 Kcu Pu / 2 Pu / 8

Table 16: Calculated controller's parameter

Controller Type Kc 𝜏𝐼 𝜏𝐷

P 1.27324

PI 1.145916 657.9167

PID 1.527887 394.75 98.6875

6.1.2. Controller tuning with process model

A process model found in Chapter 4 is used in this section to tune the PI controller. The first method is by

using approximate process model. The approximate model used is the first-order-plus-time delay transfer

function which can be seen in Figure 44.

Figure 44: Approximation transfer function

A Simulink model was built to find the parameter values of the approximation transfer function, which can

be referred in Appendix E. To obtain the best parameter values, the approximation transfer function is

compared with the process model found in Chapter 4. Trial and error method is used to find the time

delay 𝛼, the time constant 𝜏 and the gain, 𝐾. After various attempts, it found that value for 𝛼, 𝜏 and 𝐾 is

40, 590 and 0.361 that produced a result in the Figure 45. Then Table 15 is used to calculate the PI

controller parameter by using the approximation values.

55

Figure 45: Comparison between the actual and approximation model

The second method is by using autotune in PID block inside SIMULINK. The same process model in the first

method is used to auto-tune. All the PI controller parameter found in the approximation and auto-tune is

tabulated in Table 17. Then, both methods are compared with the relay tuning method found in Table 16

without the disturbance model. The disturbance model found in the experimental method was not a good

model to represent the real behaviour of the boiler system.

Table 17: PI controller parameter

Tuning method Kc 𝜏𝐼

Approximation 36.778 133.2

Autotune 2.954 292.14

Figure 46: Comparison of the PI controller without the disturbance effect

56

The initial temperature of 23.9 ⁰C inside the tank needs to be considered to simulate the real-world steam-

heated coil system. Then the set point is stepped to 35 ⁰C to test the credibility of the PI controllers. The

set point responses of PI controller design using an approximation, auto, and relay tuning are shown in

Figure 46 respectively. The approximation PI controller which indicates by green line has large overshoot

and slowly damped oscillation before reaching the steady state. Note that both PI controller from auto and

relay tune which indicated by yellow and red lines, produced longer rise time compare to approximation.

The PI controller from autotune provides a good response although it has one percent overshoot. The PI

controller from relay does not have an overshoot. However, this controller is the slowest which it takes

two hours to reach the set point compared to all the PI controller. The PI controller from autotune is the

best compared to the other two PI controllers. Then this PI controller parameter values from autotune was

implemented to steam-heated coil system

Figure 47: Result of PI controller

Based on Figure 47, the steam’s control valve opened 100% of the opening when the set point is stepped

to 35 ⁰C. When the outlet water’s temperature reached the set point value, the steam’s control valve

reduces its opening to 14% to maintain the outlet water’s temperature. This shows that the steam’s

control valve tries to regulate the opening based on the set point value. However, as the time increase, the

disturbance effect increases which can be seen in the pattern of the pressure of incoming steam. This

disturbance effects the temperature of the outlet water which it reduces the temperature to 32⁰C

although it does not have an overshoot. The outlet water’s temperature does not reach its steady state as

57

it keeps oscillating after 1 hour. The PI controller fails to maintain the temperature of the outlet water to

the desired set point due to the disturbance in the pressure of the incoming steam.

6.2. Cascade controller

A cascade controller is implemented in this thesis project due to the presence of the disturbance in the

steam-heated coil system. Both inner and outer controller is using the PI controller. The most important

fundamental of cascade design is the inner controller need to have faster response compare to outer

controller. This action can be achieved by implementing either the P or PI controller as the inner controller.

As discussed in Chapter 5, the effect of disturbance is quite severe in the heating process which causes the

temperature of the outlet water to oscillate. The presence of Integral (I) term helps to reduce the steady-

state offset produces by the Proportional (P) term, which makes it easier to analysis the performance of

inner controller to compensate the effect of the disturbance. The trial and error method is used to find the

inner and outer parameter in cascade control. The same value of 𝜏𝐼 are applied to both loop which lead to

the differences in the Kc values. As the inner loop need to have faster response, a bigger Kc value is chosen

for the inner loop. The inner need to faster response to capture the pressure drop in the steam supply

before it could affect the outlet water temperature. The cascade parameter found in trial and error

method is tabulated in Table 18.

Table 18: Cascade parameter

Cascade parameter Kc 𝜏𝐼

Outer loop 1.146 0.002

Inner loop 5 0.002

58

Figure 48: Cascade controller respond

Based on Figure 48, the temperature of outlet water (PV) indicated by red colour has no overshoot been

produced when the set point is stepped to 35 ⁰C. However, it still oscillates but not as severe compared to

step response. This oscillation causes the PV to drop to 33 ⁰C which makes the cascade controller has a

slightly better performance in maintaining the PV according to set point compares to PI controller. Also,

the steam’s control valve (MV) which indicated by black colour is very aggressive to compensate the

disturbance effect on the (PV). This aggressiveness can damage the steam control valve that indicates that

cascade controller is not suitable to reduce the disturbance effect.

This can be concluded that the controller implementation is crucial in the boiler system instead in the

steam-heated coil system. The boiler system produced a nonlinear behaviour that cannot be controlled by

using ON-OFF controller. This system requires an advanced or model predictive controller to compensate

with its nonlinearity behaviour.

59

Chapter 7

7. Summary and future work

This thesis project is started with a calibration to create the reliability of the instruments. A selection of

variables is made beforehand based on the third objectives. The temperature of the outlet water is

selected as the PV which need to be maintained at the desired temperature. The MV for the heating

process in CSHT is steam’s control valve opening and while the fixed variable is the water’s control valve.

Then, the open loop test is used to find as much information as possible about the intrinsic nature of both

systems. Based on the step response, the maximum range of the outlet water temperature is 56 ⁰C to 58

⁰C. Modelling on the steam-heated coil system is made before the effect of the disturbance on the

process. The model is simulated to verify the accuracy compared to the real steam-heated coil system.

Also, through the step response, it was found that the pressure of incoming steam has a pattern which is

produced by the boiler system. This pattern shows that the pressure of incoming steam is a disturbance

variable of the steam-heated coil system. Modelling attempts on this disturbance are made by using two

methods which are the experimental and theoretical method. In the experimental method, the pattern has

been divided into two behaviors; initial behavior and ON and OFF behavior. Then, this disturbance’s model

is tested with and without the process model which produced almost an identical result compare to the

step response except in the 40% of opening the steam control valve. The theoretical method used the

Åstöm – Bell model due to the complexity of the nonlinear in the boiler system. However, this model

cannot be used for simulation and control due to lack of the information of the boiler.

After the confirmation with the Simon Boiler company, the boiler already has its controller which is ON-

OFF controller to control the feedwater pump operation. This explains why the pressure of the incoming

steam has an ON and OFF pattern that causing the steam demand problem in the boiler system. A PI and

cascade controller is selected as a control strategy for maintaining the temperature of outlet water. For

tunning PI controller, two methods were considered which is tuning with and without the process model. A

relay tuning is used directly on the real-world system due to the absence of the process model. An

approximate and auto-tune is used when the process model is a presence. Then all PI controllers from both

methods are compared to find the best PI controller. The PI controller from the auto-tune is selected as

the best PI controller as it has the best set point response. The PI and cascade controller cannot

compensate the disturbance effect on the PV in steam-heated coil system, which they still oscillate but not

as severe compared to the step response. Cascade controller had a slightly better performance to maintain

the PV according to set point compared to PI controller. However, PI controller was the best controller in

60

overall performance compared to the cascade controller to ensure the longevity of the steam control

valve.

It was discovered that the disturbance’s model from the experimental method could not represent the real

disturbance when PI controller been implemented to it. This is because the model was designed based on

the ON and OFF state which consists of the constant period due to the feedwater pump operation. Based

on the theoretical of the boiler, it found that the pressure of incoming steam to CHT related to the drum

water level. The boiler model from the theoretical method should be used to test out the effectiveness of

the PI controller. This thesis project faced a few problems coming from the boiler system and PDCSO,

which resulted in failing to achieve the third objectives.

For future works, the boiler should be investigated alone and thoroughly without the steam-heated coil

system. The boiler is a more crucial system that requires better understanding to control it. The

disturbance model found in the theoretical method can be used as future references. The theoretical of

drum model can be used to predict the disturbance behaviour. Some information regarding the inputs and

the construction data should be obtained beforehand. The built-in ON-OFF controller in the boiler system

can be replaced for better control. Most of the research papers found during the literature review

suggested implementing the advanced control strategy in the boiler system due to nonlinear behavior. For

future work, the advanced control strategy should be considered as the feedforward, Generic Model

Control (GMC) and Internal Model Control (IMC).

61

Chapter 8

8. References

[1] B. Chindu, “Investigating and Testing Steam Usage with equipment for Teaching Process Control

Engineering in the Instrumentation and Control Engineering (ICE) Laboratory,” Murdoch University,

Perth, 2016.

[2] “Purpose of calibration ?,” Measurement Standards Laboratory of New Zealand, 2009. [Online].

Available: https://www.measurement.govt.nz/services/temperature-and-humidity/humidity-

calibration-service/calibration-certificate/purpose-of-a-. [Accessed 20 July 2017].

[3] “Getting Started with LabVIEW,” National Instruments, 2013.

[4] “System Identification Toolbox,” MathWorks, 2018. [Online]. Available:

https://www.mathworks.com/products/sysid.html. [Accessed 2 June 2018].

[5] L. Ljung, “System Identification Toolbox For Use with MATLAB,” MathWorks.

[6] “Simons SB 2S – Electric Steam Boilers,” Simons Boilers, [Online]. Available:

http://simonsboiler.com.au/product/simons-sb-2s-3-6-14-kw-electric-steam-boilers/. [Accessed 2

September 2017].

[7] S. K. a. D. Pope, “Basic Water Treatment of Steam Boilers,” Western Dry Klin Association, Perth,

2000.

[8] “Water Treatment,” [Online]. Available:

http://www.spiraxsarco.com/Documents/White%20Papers/Water_Treatment_White_Paper.pdf.

[Accessed 15 September 2017].

[9] K. J. Å. a. R. D. Bell, “Drum-boiler dynamics,” Automatica, vol. 36, 1998.

[10] A. Elguindy, “Drum-boiler control performance optimization using an observer-based state-feedback

controller within MATLAB/Simulink environment,” Bremen University, 2013.

[11] “Steam Boilers Selection Guidelines,” Chromalox Advanced Thermal Technologies, [Online].

Available: http://www.chromalox.com/en/resources-and-support/design-

tools/designguidelines/steam-boilers-selection-guidelines. [Accessed 12 September 2017].

[12] A. D. Houtz1, “Dynamic Shrink/Swell and Boiler Level Control,” Control Guru Practical Process

Control, 2015. [Online]. Available: http://controlguru.com/dynamic-shrinkswell-and-boiler-level-

control/. [Accessed 18 December 2017].

[13] “Steam Boilers,” Chipkin Automation System, [Online]. Available: http://www.chipkin.com/steam-

boilers/. [Accessed 13 September 2017].

62

[14] “Beginner's guide to Differential Pressure Transmitters,” Fuji Electric Instrumentation & Control,

[Online]. Available:

http://www.coulton.com/beginners_guide_to_differential_pressure_transmitters.html. [Accessed

19 September 2017].

[15] “Rosemount 1151 Pressure Transmitter,” Emerson, March 2010. [Online]. Available:

http://www2.emersonprocess.com/siteadmincenter/PM%20Rosemount%20Documents/00813-

0100-4360.pdf. [Accessed 20 December 2017].

[16] “Research Control Valves, CV vs Lift Chart,” Badger Meter, 2017.

[17] “ELECTROMAGNETIC FLOW METER,” KEYENCE CORPORATION, 2017. [Online]. Available:

http://www.keyence.com/ss/products/process/flowknowledge/types/electromagnetic.jsp.


[18] S. B. Reddy, “Electromagnetic FlowMeterd Working Principle,” Intrumentation Tools, 2015. [Online].

Available: http://instrumentationtools.com/electromagnetic-flow-meters-working-

principle/#.Wci7KrIjGUl. [Accessed 15 September 2017].

[19] “Steam Trap : The Complete Guide,” Forbes Marshall, 2017. [Online]. Available:

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September 2017].

[20] “Good Pipping Practice Prevents Water Hammer in Steam Systems,” ITT Industries, 1998. [Online].

Available: http://www.boydeng.com/WaterHammer.htm. [Accessed 8 June 2018].

[21] W. Sölken, “Steam and Condensate systems - Types of Steam Traps,” EWP, [Online]. Available:

http://www.wermac.org/steam/steam_part6.html. [Accessed 23 September 2017].

[22] “Inverted Bucket Steam Traps,” Xylem, 2017. [Online]. Available: http://bellgossett.com/steam-

specialties/traps/inverted-bucket-beartrap/#product-tab-overview. [Accessed 22 September 2017].

[23] “RTD sensor with "CS" head,” Correge, [Online]. Available: http://www.correge.fr/rtd-sensor-head-

type.html. [Accessed 23 September 2017].

[24] “Designing Cascade Control System with PI Controllers,” MathWorks, 2017. [Online]. Available:

https://au.mathworks.com/help/control/examples/designing-cascade-control-system-with-pi-

controllers.html?requestedDomain=au.mathworks.com&requestedDomain=au.mathworks.com.


[25] “On-Off Control,” [Online]. Available: http://www.online-

courses.vissim.us/Strathclyde/onoff_control.htm. [Accessed 18 December 2017].

[26] “What is calibration?,” Advanced Instruments, 2017. [Online]. Available:

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2017].

63

[27] B. A. Ogunnaike and W. . H. Ray, “Conventional Feedback Controller Design,” in Process Dynamics,

Modeling and Control, New York, Oxford University, 1994, pp. 555-557.

[28] B. A. Ogunnaike and W. H. Ray, in Process Dynamics, Modeling and Control, New York, Oxford

University, 1994, p. 536.

64

9. Appendices

Appendix A

Step response of both systems in the real world

The steam’s control valve is stepped to 40%, 60%, 80% and 100% of opening. The flow rate of inlet water is

3.2 l/min with a constant temperature of 23.9 °C.

Appendix A. 1: Step response when the steam's control valve is stepped to 40% of opening.

-20

0

20

40

60

80

100

120

0 1000 2000 3000 4000 5000 6000 7000 8000

Am

plit

ud

e

Time (s)






65

Appendix A. 2: Step response when the steam's control valve is stepped to 60% of opening


-20

0

20

40

60

80

100

120

0 1000 2000 3000 4000 5000 6000 7000 8000

Am

plit

ud

e

Time (s)






-20

0

20

40

60

80

100

120

0 1000 2000 3000 4000 5000 6000 7000 8000

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plit

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Time (s)






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-20

0

20

40

60

80

100

120

0 1000 2000 3000 4000 5000 6000 7000 8000

Am

plit

ud

e

Time (s)






67

Appendix B

Wiring layout

Appendix B. 1: Wiring layout of power transducer

68

Appendix C

Comparison in amplitude

Both experimental and simulation are compared based on the amplitude of the pressure of incoming steam. Note: the simulation used a P1Z transfer

function to simulate the disturbance model.

Appendix C. 1: comparison of the pressure of incoming steam between the experimental and simulation

Valve opening

(%)

Experimental amplitude

(inH20)

Simulation amplitude (inH20) Error in amplitude (inH20)

Average Based on

100% Based

on 80% Based

on 60% Based

on 40% Average Based on

100% Based

on 80% Based

on 60% Based

on 40%

40 68.025 56.09 42.2 52.66 61.92 67.5 11.94 25.825 15.365 6.105 0.525

60 93.069 84.11 63.29 78.98 92.87 101.3 8.959 29.779 14.089 0.199 -8.231

80 105 105 84.39 105 105 105 0 20.61 0 0 0

100 105 105 105 105 105 105 0 0 0 0 0

69

Appendix D

Drum boiler state equations coefficients

Note this equation found from two research papers:

𝑒11 = 𝜌𝑤 − 𝜌𝑠

𝑒12 = 𝑉𝑠𝑡

𝜕𝜌𝑠

𝜕𝑃+ 𝑉𝑤𝑡

𝜕𝜌𝑤

𝜕𝑃

𝑒21 = 𝜌𝑤ℎ𝑤 − 𝜌𝑠ℎ𝑠

𝑒22 = 𝑉𝑠𝑡 ( ℎ𝑠

𝜕𝜌𝑠

𝜕𝑃+ 𝜌𝑆

𝜕ℎ𝑠

𝜕𝑃 ) + 𝑉𝑤𝑡 ( ℎ𝑤

𝜕𝜌𝑤

𝜕𝑃+ 𝜌𝑤

𝜕ℎ𝑤

𝜕𝑃 ) − 𝑉𝑡 + 𝑚𝑡𝐶𝑝

𝜕𝑡𝑠

𝜕𝑃

𝑒32 = (𝑝𝑤 𝜕ℎ𝑤

𝜕𝑃− 𝛼𝑟ℎ𝑐

𝜕𝜌𝑤

𝜕𝑃 ) (1 − 𝑣)𝑉𝑟 + ((1 − 𝛼𝑟)ℎ𝑐

𝜕𝜌𝑠

𝜕𝑃+ 𝜌𝑠

𝜕ℎ𝑠

𝜕𝑃 ) 𝑣𝑉𝑟

+ (𝜌𝑠 + ( 𝜌𝑤 − 𝜌𝑠)𝛼𝑟)ℎ𝑐𝑉𝑟

𝜕𝑣

𝜕𝑃− 𝑉𝑟 + 𝑚𝑟𝐶𝑝

𝜕𝑡𝑠

𝜕𝑃

𝑒33 = ((1 − 𝛼𝑟)𝜌𝑠 + 𝛼𝑟𝜌𝑤)ℎ𝑐𝑉𝑟

𝜕𝑣

𝜕𝛼𝑟

𝑒42 = 𝑉𝑠𝑑

𝜕𝜌𝑠

𝜕𝑃+

1

ℎ𝑐

(𝜌𝑠𝑉𝑠𝑑

𝜕ℎ𝑠

𝜕𝑃+ 𝜌𝑤𝑉𝑤𝑑

𝜕ℎ𝑤

𝜕𝑃− 𝑉𝑠𝑑 + 𝑚𝑑𝐶𝑝

𝜕𝑡𝑠

𝜕𝑃 ) + 𝛼𝑟(1 + 𝛽)𝑉𝑟(𝑣

𝜕𝜌𝑠

𝜕𝑃+ (1 − 𝑣)

𝜕𝜌𝑤

𝜕𝑃

+ (𝜌𝑠 − 𝜌𝑤)𝜕𝑣

𝜕𝑃

𝑒43 = 𝛼𝑟(1 + 𝛽)(𝜌𝑠 − 𝜌𝑤)𝑉𝑟

𝜕𝑣

𝜕𝛼𝑟

𝑒44 = 𝜌𝑠

𝑣 = 𝜌𝑤

𝜌𝑤 − 𝜌𝑠

(1 − 𝜌𝑠

( 𝜌𝑤 − 𝜌𝑠)𝛼𝑟

ln (1 + 𝜌𝑤 − 𝜌𝑠

𝜌𝑠

𝛼𝑟))

𝑞𝑑𝑐 = √2𝜌𝑤𝐴𝑑𝑐(𝜌𝑤 − 𝜌𝑠)𝑔𝑣𝑉𝑟

𝐾

𝑞𝑐𝑡 = ℎ𝑤 − ℎ𝑓𝑤

ℎ𝑐

𝑞𝑓 + 1

ℎ𝑐

(𝜌𝑤𝑉𝑤𝑡

𝜕ℎ𝑤

𝜕𝑝+ 𝜌𝑠𝑉𝑠𝑡

𝜕ℎ𝑠

𝜕𝑝− 𝑉𝑡 + 𝑚𝑡𝐶𝑝

𝜕𝑡𝑠𝑎𝑡

𝜕𝑝 )

𝑑𝑃

𝑑𝑡

𝑞𝑟 = 𝑞𝑑𝑐 − 𝑉𝑟 (𝑣

𝜕𝜌𝑠

𝜕𝑝+ (1 − 𝑣)

𝜕𝜌𝑤

𝜕𝑝+ (𝜌𝑤 − 𝜌𝑠)

𝜕𝑣

𝜕𝑝

𝑑𝑃

𝑑𝑡) + (𝜌𝑤 − 𝜌𝑠) 𝑉𝑟

𝜕𝑣

𝜕𝛼𝑟

𝑑𝛼𝑟

𝑑𝑡

𝛾 = 𝛼𝑟

(𝜌𝑤 − 𝜌𝑠)

𝜌𝑠

𝜕𝑣

𝜕𝛼𝑟

= 𝜌𝑤

𝜌𝑠𝛾(

ln(1 + 𝛾)

𝛾−

1

1 + 𝛾)

𝜕𝑣

𝜕𝑝=

1

( 𝜌𝑤 − 𝜌𝑠)2(𝜌𝑤

𝜕𝜌𝑠

𝜕𝑝− 𝜌𝑠

𝜕𝜌𝑠

𝜕𝑝) ( 1 +

𝜌𝑤

𝜌𝑠(1 + 𝛾)−

𝜌𝑠 + 𝜌𝑤

𝛾𝜌𝑠

ln (1 + 𝛾) )

70

Appendix E

MATLAB script

The following MATLAB script refer from research paper which used Equation 6

function [ Pressure, level] = Dboiler(qs, Q, qf, P) %% Model inputs % Q = Amount of heat flow rate added to the system (Watt) % qf = Feedwater flow rate (Kg/s) % qs = Steam flow rate (Kg/s) % P = Pressure (Pascal) Vwt = 37; % Water total volume (m3) Alpha = 70; % Steam Quality (%) Vsd = 2; % Steam bubbles volume under water level (m3)

%% Drum-boiler parameters and construction data Vd = 20.204; % Drum volume (m3) Vr = 20; % Drum riser volume (m3) Vdc = 0.9; % Drum downcomer volume (m3) Vt = Vd + Vr + Vdc; % Total drum volume (m3) Ad = 20; % Drum area (m2) Adc = 0.0637; % Downcomer area (m2) mr = 1300; % Riser mass (kg) md = 1363; % Drum mass (Kg) mt = mr + md + 98888; % Total metal mass (kg) K = 25; % Friction coefficient in downcomer Td = 3; % Residence time of steam in drum (s) Beta = 0.3; % Empirical coefficient Vsd0 = 2; % Steam bubbles volume in the hypothetical situation (m3) Cp = 550; % Metal specific heat capacity ([ascal.m3/Kg.K)

%% Properties of steam and water in saturated state % Coefficients for quadratic fit to steam tables

a01 = 2.7254E6; a11 = -1.8992E4; a21 = -1160.0;

a02 = 53.1402; a12 = 7.673; a22 = 0.36;

a03 = 1.4035E6; a13 = 4.9339E4; a23 = -880.0;

a04 = 691.35; a14 = -18.672; a24 = -0.0603;

a05 = 310.6; a15 = 8.523; a25 = -0.33;

71

%% Liquid/Vapour mixture properties P1 = P*1e-5; % Pascal to Bar

%% Temperature Tfw = 104; % Feedwater (C) T_Sat = a05+(a15+a25*(P1-10))*(P1-10); % Saturation (C) dT_Sat_dP = a15+2*a25*(P1-10); % (K/Pa)

%% Density rhoV = a02+(a12+a22*(P1-10))*(P1-10); % Steam (Kg/m3) rhoL = a04+(a14+a24*(P1-10))*(P1-10); % Water (Kg/m3)

% Partial derivative with pressure drhoL_dP = a14+2*a24*(P1-10); % Water (Kg/J) drhoV_dP = a12+2*a22*(P1-10); % Steam (Kg/J)

%% Specific Enthalpy hfW = XSteam('hL_T',Tfw) * 1e3; % Feedwater (J/Kg) hL = a03+(a13+a23*a23*(P1-10))*(P1-10); % Water (J/Kg) hV = a01+(a11+a21*(P1-10))*(P1-10); % Steam (J/Kg) hC = hV - hL; % Condensation (J/Kg)

% Partial derivative with pressure dhL_dP = a13+2*a23*(P1-10); % Water (J/Kg.Pa) dhV_dP = a11+2*a21*(P1-10); % Steam (J/Kg.Pa)

%% Coefficients values Eta = (Alpha*(rhoL - rhoV))/rhoV; AlphaV = (rhoL / (rhoL - rhoV)) * (1 - ((rhoV/((rhoL - rhoV)*Alpha)) * log

(1+(((rhoL - rhoV)*Alpha)/rhoV)))); dAlphaV_dP = (1/((rhoL - rhoV)^2))*(rhoL*drhoV_dP - rhoV*drhoL_dP)* (1 +

(rhoL/(rhoV*(1+Eta))) - (((rhoV+rhoL)*log(1+Eta))/(rhoV*Eta))); dAlphaV_dAlpha = (rhoL/(rhoV*Eta))*(((1/Eta)*log(1+Eta)) - (1/(1+Eta))); qdc = sqrt((2*rhoL*Adc*(rhoL - rhoV)*9.81*AlphaV*Vr)/K); Vwd = Vwt -Vdc -(1-AlphaV)*Vr;

%% State equations coeeficients

e11 = rhoL - rhoV; e12 = Vwt*drhoL_dP + (Vt - Vwt)*drhoV_dP; e21 = rhoL*hL - rhoV*hV; e22 = Vwt*(hL*drhoL_dP + rhoL*dhL_dP) + ( Vt - Vwt)*(hV*drhoV_dP +

rhoV*dhV_dP) - Vt + mt*Cp*dT_Sat_dP; e32 = (rhoL*dhL_dP - Alpha*hC*drhoL_dP)*(1-AlphaV)*Vr+ ((1-

Alpha)*hC*drhoV_dP + rhoV*dhV_dP)*AlphaV*Vr + (rhoV + (rhoL -

rhoV)*Alpha)*hC*Vr*dAlphaV_dP - Vr + mr*Cp*dT_Sat_dP; e33 = ((1-Alpha)*rhoV + Alpha*rhoL)*hC*Vr*dAlphaV_dAlpha; e42 = Vsd*drhoV_dP + (1/hC)*(rhoV*Vsd*dhV_dP + rhoL*Vwd*dhL_dP - Vsd - Vwd

+ md*Cp*dT_Sat_dP) + Alpha*Vr*(1+Beta)*(AlphaV*drhoV_dP + (1-

AlphaV)*drhoL_dP + (rhoV-rhoL)*dAlphaV_dP); e43 = Alpha*(1+Beta)*(rhoV-rhoL)*Vr*dAlphaV_dAlpha; e44 = rhoV;

%% State variables dP_dt = (1/(e11*e22 - e12*e21))*(e11*Q + qf*(hfW*e11 -e21) + qs*(e21 -

hV*e11));

72

dVwt_dt = (1/(e11*e22 - e12*e21))*(qf*(e22 - hfW*e12) + qs*(hV*e12 - e22) -

e12*Q); dAlpha_dt = (1/e33)*(Q - Alpha*hC*qdc - e32*dP_dt); dVsd_dt = (1/e44)*(((rhoV/Td)*(Vsd0-Vsd)) + ((hfW -hL)*qf/hC) - e42*dP_dt -

e43*dAlpha_dt); Level = (Vwd + Vsd)/ Ad - 0.875;

%% Model outputs Pressure = P1 + dP_dt; level = Level;

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