essential process control for chemical engineers

DR. BRUCE POSTLETHWAITE

ESSENTIAL PROCESS
CONTROL FOR
CHEMICAL ENGINEERS

2


Essential Process Control for Chemical Engineers
1st edition
© 2017 Dr. Bruce Postlethwaite & bookboon.com
ISBN 978-87-403-1655-1
Peer reviewed by Dr. Iain Burns, Senior Lecturer, Director of Teaching, University of
Strathclyde

3


ESSENTIAL PROCESS CONTROL
FOR CHEMICAL ENGINEERS

CONTENTS

CONTENTS
Foreword

8

Introduction

9

Main Learning points

9

1.1

Why do we need control?

9

2

Instrumentation

12

Main learning points

12

2.1

What is an instrument?

12

2.2

Factors to be considered in selecting an instrument

13

2.3

Instruments for temperature measurement

17

2.4

Pressure measurement

20

2.5

Flow measurement

23

2.6

Level measurement

27

2.7

Chemical composition

30

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ESSENTIAL PROCESS CONTROL
FOR CHEMICAL ENGINEERS

3

CONTENTS

Communication signals

32

Main learning points

32

3.1

Types of communication signal

32

4

Final control elements

39

Main Learning points

39

4.1

Control valves

39

4.2

Control valve sizing

41

5

Diagrams for process control systems

48

Main learning points

48

5.1

Process flow diagrams (PFDs)

48

5.2

Piping and instrumentation diagrams (P&IDs)

49

6

Inputs and outputs in control systems

55

Main learning points

55

6.1

Process inputs

55

6.2

Process outputs

56

6.3

Processes in control engineering

57

6.4

An example of variables and processes

58

7

Introduction to feedback control

59

Main learning points

59

7.1

Feedback control and block diagrams

59

7.2

Positive and negative feedback

61

7.3

Control loop problems

61

7.4

Direction of control action

64

7.5

Controller hardware

66

8

Introduction to steady-state and dynamic response

70

Main learning points

70

8.1

Steady-state gain

70

8.2

Dynamic response

73

5


ESSENTIAL PROCESS CONTROL
FOR CHEMICAL ENGINEERS

9

CONTENTS

Dynamic modelling

87

Main learning points

87

9.1

Laplace transforms

88

9.2

Derivation of basic transforms

88

9.3

Solution of differential equations using Laplace transforms

91

9.4

Transfer functions

93

9.5

Block Diagrams

94

9.6

Block diagram algebra

95

9.7

Solutions of responses for high-order systems

95

9.8

Forming dynamic models

100

10

Analytical solution of real world models

106

Main learning points

106

10.1

Types of non-linearity

106

10.2

Linearisation of non-linear equations

107

10.3

Simplifying expressions through deviation variables

110

10.4

Procedure for simplifying and solving a non-linear model

112

10.5

Putting it all together – a reactant balance for a CSTR

112

11

PID Controller algorithm

117

Main learning points

117

11.1

Really simple feedback controller – on-off

118

11.2

Proportional-integral-derivative (PID) control

119

11.3

Proportional only control

121

11.4

Integral only control

126

11.5

Derivative action

127

11.6

Proportional-Intergral (PI) control

130

11.7

PID control response

131

11.8

Other forms of PID algorithm

133

12

Control system analysis

137

Main learning points

137

12.1

Analysis of a typical feedback control system

137

12.2

The PID algorithm as a transfer function

139

12.3

Analysis of proportional control of a first-order process

140

12.4

Example of a first order process under proportional control

142

12.5

Example of a second-order process under proportional control

145

12.6

Analysis of integral control of a first-order process

148

6


ESSENTIAL PROCESS CONTROL
FOR CHEMICAL ENGINEERS

CONTENTS

13

Controller tuning

149

Main learning points

149

13.1

What needs to be done to tune a PID Controller?

149

13.2

How do you decide what is a good controller performance?

150

13.3

Some methods of controller tuning

154

13.4

Control loop health monitoring

161

13.5

Control loop diagnostics

162

14

More advanced single-loop control arrangements

163

Main learning points

163

14.1

Cascade control

163

14.2

Selective or autioneering control

167

14.3

Override control

169

14.4

Ratio control

172

14.5

Feedforward control

173

15

Design of control systems

181

Main learning points

181

15.1

Control envelope

181

15.2

Multivariable processes

184

15.3

How to determine the number of controlled variables

185

15.4

Plantwide mass balance control

191

16

Control system architecture

194

Main learning points

194

16.1

The effect of technology on process plant control rooms

194

16.2

Human factors in control room displays

197

16.3

Distributed control systems

200

16.4

Safety Instrumented Systems

201

17

Bibliography

202

Acknowledgements

203

Appendix

204

The use of software for teaching process control at

Strathclyde University

204

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ESSENTIAL PROCESS CONTROL
FOR CHEMICAL ENGINEERS

FOREWORD

FOREWORD
his book is based on the course notes from the introductory process control class at
Strathclyde University in Glasgow, Scotland. his course is itself based on the IChemE
model-curriculum for chemical engineers and covers the material that ALL chemical engineers
are supposed know. he IChemE curriculum was drawn up by a team of industrialists and
academics, led by Professor Jon Love, in response to a recognised need for chemical engineers
to be taught a more industrially relevant course.
his book isn’t a traditional academic textbook in that there are no references anywhere
in the text. he main reason for this is that the material has been gathered from many
diferent sources after a working lifetime of teaching in the area and trying to identify an
original source is impossible. I have included a bibliography for readers who wish to look
further into the subject.
I hope students and teachers ind this book useful. A major new part of the course at
Strathclyde University (where I teach) has been the introduction of new process control
learning software called PISim, and this is described in the appendix. PISim will be
commercially released in late Autum 2017.

8

ESSENTIAL PROCESS CONTROL
FOR CHEMICAL ENGINEERS

1

INTRODUCTION

INTRODUCTION

MAIN LEARNING POINTS
• Why process control is necessary
Process control is concerned with making sure that processes do what they are supposed
to in a safe and economical way. his isn’t an easy task as most processes are subject to
many inputs called disturbances that constantly cause the controlled variables to move
away from their desired values (or setpoints). To prevent this other process inputs called
manipulations have to be moved to restore the process to the desired state.
Process control is concerned with the overall system. A control engineer has to know about the
instruments used to measure process quantities, the valves and other inal control elements
that allow control systems to adjust the process, communications to transmit information
around, the control algorithms that decide how to respond to the information coming
from the process, and inally the control engineer needs to understand how the process
itself behaves: not just its steady-state behaviour but more importantly its dynamic response.
Control engineering is now an area which ofers big career opportunities for chemical
engineers. he area used to be dominated by electrical/electronic engineers as the major
challenges were in the hardware. his has changed. Sophisticated modern control systems
allow much more complicated, process related, control schemes and now a major
requirement for a control engineer is that they have a good understanding of the process.

1.1

WHY DO WE NEED CONTROL?

Figure 1 – a pressure trace from a SCADA system

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ESSENTIAL PROCESS CONTROL
FOR CHEMICAL ENGINEERS

INTRODUCTION

• In real chemical plants, steady-state doesn’t exist. hings are always changing.
Temperatures move up and down, levels get lower and higher, etc (see igure 1).
• All processes are subject to disturbances. hese are inputs to the process that change
in a way that is beyond the reach of the local control system. A rainstorm on the
outside of a distillation column will cool the column and require action to be
taken to increase the heat input. Raw material variations are another common
disturbance. Actions of other control systems can also cause disturbances to the
process of interest – if a control system upstream or downstream of a process reduces
a lowrate its efects will cascade throughout the rest of the process.
• he control system needs to actively regulate against the efects of these disturbances.
It does this by either measuring the disturbances directly (where this is possible and
economic) or by measuring their efects on the controlled variables of the process. It
then makes adjustments to other inputs to the process called manipulated variables
to try to reduce or eliminate the efects of the disturbances. When controllers are
holding controlled variables at ixed setpoints they are said to be in regulator or
disturbance rejection mode.

• Process don’t suddenly start at their lowsheet conditions, they don’t shut down
on their own and don’t change production rate, etc without active intervention
from control systems. When these major changes are being made to a process, the
controllers will be acting in a setpoint tracking or servo mode. In servo mode, a
controller will be trying to make the controlled variable track a moving setpoint.
• Control systems also have a major part to play in process safety. he basic control
system will usually ensure that the process stays within acceptable limits and will
be equipped with alarms to warn operators of any problems. Interlocks may also
be present in the basic system. hese are used to lock particular inputs when other
conditions are in existence. For example, the access doors to a kiln may be locked
by a control system if the internal temperature is dangerously high. In extreme
circumstances, special control systems (called safety instrumented systems or SIS ) that
are separate from the normal process control system may come into play. hese
may be local to a particular piece of equipment, for example a high-temperature
trip on a pump motor; or may have a process or plant-wide focus, for example an
emergency shutdown system.

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ESSENTIAL PROCESS CONTROL
FOR CHEMICAL ENGINEERS

INTRODUCTION

• Finally, good control saves money. Plants are normally operated close to constraints
(e.g. the acceptable product quality). Poor control means more variability and
this means that the mean value of a controlled variable needs to be held further
from the constraint than is necessary with good control. Figure 2 shows a simple
example – the tops quality from a distillation column. his may have a limit on

the lowest acceptable composition and it’s the responsibility of the control system
to hold the composition about this limit. If the control is poor and there’s lots of
variability, then it will be necessary to set an average value of composition much
higher than if good control is used. his higher average composition will lead to
increased relux going down the column and hence more vapour having to be
generated by the reboiler, which increases steam costs.

Figure 2 – The advantage of good control

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ESSENTIAL PROCESS CONTROL
FOR CHEMICAL ENGINEERS

2

INSTRUMENTATION

INSTRUMENTATION

MAIN LEARNING POINTS
• Factors involved in selecting instrumentation
• Techniques for temperature, pressure, low and level measurements
he instruments on a chemical plant are the devices used to monitor the important variables
that allow the condition of the process to be determined.

2.1

WHAT IS AN INSTRUMENT?

Transducers or sensors are the primary sensing elements. hey are devices that convert some
physical quantity that we want to measure (e.g. temperature, pressure, etc). into some sort
of signal that can be processed further. For example, a thermocouple converts a temperature
diference into a voltage; a piezo resistive pressure sensor converts a pressure into a change
in electrical resistance.

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ESSENTIAL PROCESS CONTROL
FOR CHEMICAL ENGINEERS

INSTRUMENTATION

Signal conditioning is the signal processing that is applied to the output of the transducer.
Sometimes this could simply be ampliication, but often more complicated things like
linearisation are required (ideally, the output of a device should change linearly with changes
in the quantity being measured). Modern instruments such as Coriolis lowmeters have very
complicated signal processing build into them to detect the phase shifts in the motion of
the sensing elements.

A transmitter is a device that converts the output from signal conditioning into a signal
that is compatible with the communication system being used in the plant. here are many
diferent standards in use ranging from 4-20mA analogue signals up to digital Fieldbus
systems – these will be discussed later.
An instrument is a device that contains at least one but usually more, and often all of
the above (transducer, signal conditioning and transmitter). An instrument is a complete
measurement package that senses the quantity to be measured and presents that measurement
in a form suitable for use (e.g. a simple instrument might be a Bourdon gauge for pressure
measurement – the transducer, a helical metal tube, distorts with pressure and drives the
gauge needle directly; a more typical instrument for modern chemical plants might be a
packaged RTD (resistance temperature device) – it will include the RTD, signal conditioning,
and a transmitter).

2.2

FACTORS TO BE CONSIDERED IN SELECTING AN INSTRUMENT

2.2.1 RANGE

he range of an instrument is range of the measured quantity over which the instrument
will give a reliable output. he range is always the same or bigger than the span of an
instrument. While an instrument with a large range might seem to be always desirable this
isn’t usually the case in practice. he sensitivity (change in output vs change in measurement)
of transducers drops signiicantly in large range devices leading to reduced accuracy.
2.2.2 SPAN

he span of an instrument is an adjustable parameter (there will be a button, screw or
software link on the instrument that will allow the adjustment). he span is the distance
the measured quantity has to move to drive the instrument output from its minimum value
to its maximum (remember that instrument outputs match communication standards which

have ixed maximum and minimum values). By adjusting the span, the instrument’s sensitivity
(output change vs. input change) can be altered – large spans will lead to lower sensitivities.

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ESSENTIAL PROCESS CONTROL
FOR CHEMICAL ENGINEERS

INSTRUMENTATION

2.2.3 ACCURACY AND PRECISION

All measurement instruments are subject to random error – if you take repeated measurements
of a ixed quantity you will always get a scatter of values about a mean. An accurate
instrument is one where the mean is centred close to the actual value of the quantity being
measured. An instrument can be accurate, but still have a signiicant amount of error on an
individual measurement – the accurate mean can only be obtained by taking many repeat
measurements. A precise instrument is one which, when measuring a constant quantity,
returns output values which are very close to one another – the scatter between readings
is small. It is possible for an instrument to be precise (high repeatability in measurement)
but not accurate (with the mean some distance away from the true value of the quantity
being measured). An ideal instrument is one which is both precise and accurate.

Figure 3 – accuracy and precision

2.2.4 REPEATABILITY AND DRIFT

In most instruments repeatability and precision mean the same thing. However, some sensors
sufer from hysteresis. In these sensors the measurement is afected by what the variable being

measured was doing prior to the measurement. It is most prevalent in systems which involve
some sort of mechanical element in their sensing. For example, bourdon pressure sensors
usually exhibit hysteresis – the measurement they produce will be diferent if the pressure
was rising or falling immediately prior to the measurement.
Drift is a medium to long term efect that causes some instruments to lose mainly accuracy, but
also possibly precision. For example, corrosion of a thermocouple will alter its thermoelectric
properties and hence the voltage produced at a particular temperature.

14