Fundamentals of Process Control: Principles and Concepts offers an introduction to how engineers and technicians ensure that industrial processes, such as heating, mixing or pumping, are safe and efficient. It covers core concepts, including what a process is, how feedback control loops work and why measurements, valves and controllers matter.
This book also provides practical tools, including proportional-integral-derivative (PID) tuning, cascade and ratio control and statistical methods for measuring and reducing variability. Later chapters introduce modeling and simulation, along with more advanced topics such as adaptive and fuzzy logic control, all grounded in clear examples and step-by-step explanations. Designed for learners and practitioners, this book strikes a balance between real-world applications and the key math and science necessary to understand and design control systems.
Table of Contents:
Preface xvii
About the Author xxi
Section 1 Principles and Concepts 1
Chapter 1 Introduction and Overview 3
1.1 History 4
1.2 What Is Process Control? 4
1.3 Process Intend 6
1.4 Why Study Process Control? 8
1.5 Control Strategies 9
1.6 Process Design 10
1.7 Conservation of Mass and Energy 10
1.8 Concepts of Calculus 11
1.9 Process Documentation 15
1.10 Units 17
1.11 Process Variables 18
1.12 Summary 31
Chapter 2 Basic Control Concepts 33
2.1 Process and Process Control 33
2.2 The Process 35
2.3 The Control Loop Concept 37
2.4 Summary 40
2.5 Exercises 40
Chapter 3 The Control Loop 43
3.1 A Typical Feedback Control Loop 43
3.2 The Three Tasks 44
3.3 Process Instruments 46
3.4 Elements of a Closed-Loop System 49
3.5 Process Control Terms 50
3.6 Combining Functions in a Single Instrument 54
3.7 Summary 54
3.8 Exercise 55
Chapter 4 Functional Structure of Feedback Control 57
4.1 The Transfer Function 57
4.2 Block Diagrams 58
4.3 The Functional Layout of a Feedback Control Loop 61
4.4 Mathematics of Block Diagrams 62
4.5 Gain and Sensitivity 63
4.6 Process Gain 72
4.7 Summary 73
4.8 Exercises 74
Chapter 5 Dynamics of Systems 75
5.1 Dynamic Components 76
5.2 First-Order Lag 77
5.3 Time Constants 79
5.4 Elements of Systems 83
5.5 Dead Time 88
5.6 First-Order plus Dead Time 91
5.7 Higher Order Systems 92
5.8 Closed-Loop versus Open-Loop Response 94
5.9 Sensor Dynamics 97
5.10 Actuator Dynamics 99
5.11 Process Gain and Time Constant 101
5.12 Summary 109
5.13 Exercises 110
Chapter 6 Process Characteristics 113
6.1 Introduction 113
6.2 The Integral or Ramp Process 116
6.3 First-Order Lag Process 123
6.4 Second-Order Lag Process 134
6.5 Summary 140
Chapter 7 Sensors, Transducers, and Transmitters 141
7.1 The Sensor, Transducer, and Transmitter 141
7.2 Selection of Measuring Devices 143
7.3 Accuracy and Precision 144
7.4 Sensitivity, Resolution, Repeatability, and Reproducibility 150
7.5 Rangeability and Turndown Ratio 152
7.6 Measurement Uncertainty Analysis 152
7.7 Transmission Systems 153
7.8 The 4 to 20 mA Current Loop 157
7.9 Smart Sensors 159
7.10 Summary 159
7.11 Exercises 160
Chapter 8 Actuators and Final Control Elements 161
8.1 Introduction 161
8.2 Control Valves and Actuators 162
8.3 Control Valve Selection and Sizing 171
8.4 Motors 173
8.5 Pumps 182
8.6 Solenoids 186
8.7 Summary 188
8.8 Exercises 188
Chapter 9 Controllers 191
9.1 The PID Controller 191
9.2 On-Off Control 194
9.3 Proportional Control 198
9.4 Integral (Reset) Control 209
9.5 Differential (Rate) Control 214
9.6 PID Control 217
9.7 Summary 220
9.8 Exercises 222
Chapter 10 Tuning Control Loops 225
10.1 Know Your Controller 226
10.2 Criteria of Good Control 228
10.3 The Tuning Concept 229
10.4 Closed-Loop Tuning Methods 231
10.5 The Process Reaction Curve 234
10.6 A Simple Open-Loop Method (Ziegler-Nichols) 236
10.7 The Need to Retune and Adaptive Tuning 239
10.8 Summary 240
10.9 Exercises 240
Section 2 Control Strategies 241
Chapter 11 Cascade Control 243
11.1 The Concept of Cascade Control 243
11.2 Applications 246
11.3 Implementing Cascade Control 250
11.4 Selection of Cascade Controller Modes and Tuning 251
11.5 Summary 252
11.6 Exercises 253
Chapter 12 Feedforward Control 255
12.1 Feedforward Control 255
12.2 Steady-State Feedforward Control 258
12.3 Steady-State or Dynamic Feedforward Control 262
12.4 General Feedforward Control 264
12.5 Combined Feedforward and Feedback Control 265
12.6 Summary 267
12.7 Exercises 267
Chapter 13 Multivariable Control 269
13.1 The Multivariable Control Concept 269
13.2 Implementing Multivariable Control 271
13.3 Summary 273
13.4 Exercises 273
Chapter 14 Ratio Control 275
14.1 The Ratio Control Concept 275
14.2 Applying Ratio Control 277
14.3 Summary 279
14.4 Exercises 279
Chapter 15 Special Control Strategies 281
15.1 Introduction 281
15.2 Three-Element Boiler Control 283
15.3 Selective, Override, and Split-Range Control 285
15.4 Summary 294
15.5 Exercises 294
Chapter 16 Statistical Process Control 295
16.1 Introduction 296
16.2 Statistics (Mean and Standard Deviation) 296
16.3 The Tools of SPC 303
16.4 Statistical Process Optimization 306
16.5 Summary 306
16.6 Exercises 307
Chapter 17 Fuzzy Logic Control 309
17.1 Origin of Fuzzy Logic 309
17.2 What Is Fuzzy Logic? 310
17.3 Operating Rules 310
17.4 Linguistic Variables 312
17.5 Defuzzification 314
17.6 Single-Input Control Example 314
17.7 Two-Input Control System Example 320
17.8 Summary 325
Section 3 Advanced Topics 327
Chapter 18 Process Modeling and Simulation 329
18.1 Introduction 329
18.2 How to Build a Model 331
18.3 Differential Equations of Physical Systems 332
18.4 Case Study: Direct Current Motor 333
18.5 Case Study: Two-Tank Level Control (Revisited) 340
18.6 Simulating Control Objective 343
18.7 Summary 344
Chapter 19 Model-Based Control 345
19.1 Introduction 345
19.2 Dead Time 346
19.3 The Smith Predictor Algorithm 349
19.4 Lambda Tuning 353
19.5 Summary 355
19.6 Exercise 355
Chapter 20 Nonlinear and Adaptive Control 357
20.1 Nonlinearity 358
20.2 Valve Characteristics 359
20.3 Process Characteristics 360
20.4 Adaptive Control 363
20.5 Adaptive Gain Control 365
20.6 Three-Mode Adaptive Tuning 367
20.7 Summary 367
20.8 Exercises 368
Chapter 21 Control System Architecture 369
21.1 Basic Components 370
21.2 System Components 372
21.3 Historical Perspective 374
21.4 Distributed Control Systems 381
21.5 Supervisory Control and Data Acquisition 386
21.6 Sequential or Batch Control 388
21.7 Summary 388
Chapter 22 Digital Systems 389
22.1 Hardware Elements 390
22.2 What Is Digital Signal Processing? 392
22.3 Digital Signals 394
22.4 Mathematical Operations on Discrete Signals 399
22.5 Design of Digital Control Systems 404
22.6 Design and Implementation of a PID Controller 408
22.7 Computer Implementation 412
22.8 The Z-Transform 413
22.9 Bilinear Transform 420
22.10 Summary 422
Appendix A: System of Units 423
Appendix B: Graphic Symbols for Process Measurement and Control 433
Appendix C: The Laplace Transform 447
Appendix D: Exercise Solutions 455
Bibliography 477
Index 481
About the Author :
Patrick F. Bouwman is a semiretired electrical engineer with over 40 years of industrial experience, including 18 years in the design and development of military electronics, instrumentation, and biomedical equipment. For more than 15 years, Bouwman operated his own company specializing in research, design, and development of data acquisition and signal processing systems for medical research applications and the instrumentation and process industry. He has provided design and consulting services to the process and automation industry and participated in research conducted at McGill University by custom designing data acquisition equipment and instrumentation for medical research applications.
In addition, Bouwman taught industrial electronics at the collegiate level for over 20 years and was department chair for 16 years, a role in which he was actively involved in all facets of curriculum development, laboratory design, industrial training, and continuing education. He has written numerous instructional and lab manuals on topics including analog and digital electronics, signal processing, discrete automation, instrumentation, process control, PLC programming, ISA-5.1 technical documentation, robotics, computer automation, distributed automation, and medical and military electronics.
He has also provided technical training and instructional material to the Canadian Armed Forces; conducted seminars in data acquisition, signal processing, instrumentation, and control for the manufacturing industry; and prepared and conducted seminars/workgroups in instrumentation, process control, and ISA-5.1 for the International Society of Automation (ISA) Montreal Section. Bouwman is a senior member of ISA, and he served on the Montreal Section board of directors.
He received a B.Sc. in electrical and electronic engineering from Concordia University in Montreal in 1976, and he currently lives in Montreal, Canada.
