Practical Process Control for Engineers and Technicians

By: Altmann

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Paperback | 17 March 2005

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304 Pages

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25.4 x 18.42 x 2.54

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This book is aimed at engineers and technicians who need to have a clear, practical understanding of the essentials of process control, loop tuning and how to optimize the operation of their particular plant or process. The reader would typically be involved in the design, implementation and upgrading of industrial control systems. Mathematical theory has been kept to a minimum with the emphasis throughout on practical applications and useful information.

This book will enable the reader to:
* Specify and design the loop requirements for a plant using PID control
* Identify and apply the essential building blocks in automatic control
* Apply the procedures for open and closed loop tuning
* Tune control loops with significant dead-times
* Demonstrate a clear understanding of analog process control and how to tune analog loops
* Explain concepts used by major manufacturers who use the most up-to-date technology in the process control field

· A practical focus on the optimization of process and plant
· Readers develop professional competencies, not just theoretical knowledge
· Reduce dead-time with loop tuning techniques

Industry Reviews

"This book is aimed at engineers and technicians who need to have a clear, practical understanding of the essentials of process control, loop tuning and how to optimize the operation of their particular plant or process." --Chemical Engineering Progress

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Preface	p. xi
Introduction	p. 1
Objectives	p. 1
Introduction	p. 1
Basic definitions and terms used in process control	p. 2
Process modeling	p. 2
Process dynamics and time constants	p. 5
Types or modes of operation of process control systems	p. 13
Closed loop controller and process gain calculations	p. 15
Proportional, integral and derivative control modes	p. 16
An introduction to cascade control	p. 16
Process measurement and transducers	p. 18
Objectives	p. 18
The definition of transducers and sensors	p. 18
Listing of common measured variables	p. 18
The common characteristics of transducers	p. 19
Sensor dynamics	p. 21
Selection of sensing devices	p. 21
Temperature sensors	p. 22
Pressure transmitters	p. 28
Flow meters	p. 35
Level transmitters	p. 42
The spectrum of user models in measuring transducers	p. 44
Instrumentation and transducer considerations	p. 45
Selection criteria and considerations	p. 48
Introduction to the smart transmitter	p. 50
Basic principles of control valves and actuators	p. 52
Objectives	p. 52
An overview of eight of the most basic types of control valves	p. 52
Control valve gain, characteristics, distortion and rangeability	p. 67
Control valve actuators	p. 71
Control valve positioners	p. 76
Valve sizing	p. 76
Fundamentals of control systems	p. 78
Objectives	p. 78
On-off control	p. 78
Modulating control	p. 79
Open loop control	p. 79
Closed loop control	p. 81
Deadtime processes	p. 84
Process responses	p. 85
Dead zone	p. 86
Stability and control modes of closed loops	p. 87
Objectives	p. 87
The industrial process in practice	p. 87
Dynamic behavior of the feed heater	p. 88
Major disturbances of the feed heater	p. 88
Stability	p. 89
Proportional control	p. 90
Integral control	p. 93
Derivative control	p. 95
Proportional, integral and derivative modes	p. 98
I.S.A vs 'Allen Bradley'	p. 98
P, I and D relationships and related interactions	p. 98
Applications of process control modes	p. 99
Typical PID controller outputs	p. 99
Digital control principles	p. 100
Objectives	p. 100
Digital vs analog: a revision of their definitions	p. 100
Action in digital control loops	p. 100
Identifying functions in the frequency domain	p. 101
The need for digital control	p. 103
Scanned calculations	p. 105
Proportional control	p. 105
Integral control	p. 105
Derivative control	p. 106
Lead function as derivative control	p. 106
Example of incremental form (Siemens S5-100 V)	p. 107
Real and ideal PID controllers	p. 108
Objectives	p. 108
Comparative descriptions of real and ideal controllers	p. 108
Description of the ideal or the non-interactive PID controller	p. 108
Description of the real (Interactive) PID controller	p. 109
Lead function - derivative control with filter	p. 110
Derivative action and effects of noise	p. 110
Example of the KENT K90 controllers PID algorithms	p. 111
Tuning of PID controllers in both open and closed loop control systems	p. 112
Objectives	p. 112
Objectives of tuning	p. 112
Reaction curve method (Ziegler-Nichols)	p. 114
Ziegler-Nichols open loop tuning method (1)	p. 116
Ziegler-Nichols open loop method (2) using POI	p. 117
Loop time constant (LTC) method	p. 119
Hysteresis problems that may be encountered in open loop tuning	p. 120
Continuous cycling method (Ziegler-Nichols)	p. 120
Damped cycling tuning method	p. 123
Tuning for no overshoot on start-up (Pessen)	p. 126
Tuning for some overshoot on start-up (Pessen)	p. 127
Summary of important closed loop tuning algorithms	p. 127
PID equations: dependent and independent gains	p. 127
Controller output modes, operating equations and cascade control	p. 131
Objectives	p. 131
Controller output	p. 131
Multiple controller outputs	p. 132
Saturation and non-saturation of output limits	p. 133
Cascade control	p. 134
Initialization of a cascade system	p. 136
Equations relating to controller configurations	p. 136
Application notes on the use of equation types	p. 139
Tuning of a cascade control loop	p. 140
Cascade control with multiple secondaries	p. 141
Concepts and applications of feedforward control	p. 142
Objectives	p. 142
Application and definition of feedforward control	p. 142
Manual feedforward control	p. 143
Automatic feedforward control	p. 143
Examples of feedforward controllers	p. 144
Time matching as feedforward control	p. 144
Combined feedback and feedforward control	p. 147
Objectives	p. 147
The feedforward concept	p. 147
The feedback concept	p. 147
Combining feedback and feedforward control	p. 148
Feedback-feedforward summer	p. 148
Initialization of a combined feedback and feedforward control system	p. 149
Tuning aspects	p. 149
Long process deadtime in closed loop control and the Smith Predictor	p. 150
Objectives	p. 150
Process deadtime	p. 150
An example of process deadtime	p. 151
The Smith Predictor model	p. 152
The Smith Predictor in theoretical use	p. 153
The Smith Predictor in reality	p. 153
An exercise in deadtime compensation	p. 154
Basic principles of fuzzy logic and neural networks	p. 155
Objectives	p. 155
Introduction to fuzzy logic	p. 155
What is fuzzy logic?	p. 156
What does fuzzy logic do?	p. 156
The rules of fuzzy logic	p. 156
Fuzzy logic example using five rules and patches	p. 158
The Achilles heel of fuzzy logic	p. 159
Neural networks	p. 159
Neural back propagation networking	p. 161
Training a neuron network	p. 162
Conclusions and then the next step	p. 163
Self-tuning intelligent control and statistical process control	p. 165
Objectives	p. 165
Self-tuning controllers	p. 165
Gain scheduling controller	p. 166
Implementation requirements for self-tuning controllers	p. 167
Statistical process control (SPC)	p. 167
Two ways to improve a production process	p. 168
Obtaining the information required for SPC	p. 169
Calculating control limits	p. 173
The logic behind control charts	p. 175
Some Laplace transform pairs	p. 176
Block diagram transformation theorems	p. 179
Detail display	p. 181
Auxiliary display	p. 185
Configuring a tuning exercise in a controller	p. 188
Installation of simulation software	p. 190
Operation of simulation software	p. 193
Configuration	p. 197
General syntax of configuration commands	p. 198
Configuration commands	p. 199
Algorithms	p. 208
Background graphics design	p. 223
Configuration example	p. 224
Introduction to exercises	p. 229
Flow control loop - basic example	p. 231
Proportional (P) control- flow chart	p. 234
Integral (I) Control - flow control	p. 237
Proportional and integral (PI) control - flow control	p. 240
Introduction to derivative (D) control	p. 242
Practical introduction into stability aspects	p. 246
Open loop method - tuning exercise	p. 252
Closed loop method - tuning exercise	p. 256
Saturation and non-saturation output limits	p. 260
Ideal derivative action - ideal PID	p. 263
Cascade control	p. 267
Cascade control with one primary and two secondaries	p. 271
Combined feedback and feedforward control	p. 276
Deadtime compensation in feedback control	p. 279
Static value alarm	p. 284
Index	p. 286
Table of Contents provided by Ingram. All Rights Reserved.

Practical Process Control for Engineers and Technicians

At a Glance

Paperback

Industry Reviews

Shipping

How to return your order

Defective items

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