Process Dynamics and Control. 3rd Edition International Student Version

  • ID: 2243080
  • Book
  • Region: Global
  • 464 Pages
  • John Wiley and Sons Ltd
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This third edition provides chemical engineers with process control techniques that are used in practice while offering detailed mathematical analysis. Numerous examples and simulations are used to illustrate key theoretical concepts. New exercises are integrated throughout several chapters to reinforce concepts. Up–to–date information is also included on real–time optimization and model predictive control to highlight the significant impact these techniques have on industrial practice. And chemical engineers will find two new chapters on biosystems control to gain the latest perspective in the field.
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PART ONE INTRODUCTION TO PROCESS CONTROL

1. Introduction to Process Control 1

1.1 Representative Process Control Problems 1

1.2 Illustrative Example A Blending Process 3

1.3 Classification of Process Control Strategies 5

1.4 A More Complicated Example A Distillation Column 7

1.5 The Hierarchy of Process Control Activities 8

1.6 An Overview of Control System Design 10

2. Theoretical Models of Chemical Processes 15

2.1 The Rationale for Dynamic Process Models 15

2.2 General Modeling Principles 17

2.3 Degrees of Freedom Analysis 21

2.4 Dynamic Models of Representative Processes 22

2.5 Process Dynamics and Mathematical Models 35

PART TWO DYNAMIC BEHAVIOR OF PROCESSES

3. Transfer Function Models 43

3.1 An Illustrative Example: A Continuous Blending System 43

3.2 Transfer Functions of Complicated Models 45

3.3 Properties of Transfer Functions 46

3.4 Linearization of Nonlinear Models 49

4. Dynamic Behavior of First–Order and Second–Order Processes 58

4.1 Standard Process Inputs 58

4.2 Response of First–Order Processes 61

4.3 Response of Integrating Processes 64

4.4 Response of Second–Order Processes 66

5. Dynamic Response Characteristics of More Complicated Processes 78

5.1 Poles and Zeros and Their Effect on Process Response 78

5.2 Processes with Time Delays 82

5.3 Approximation of Higher–Order Transfer Functions 86

5.4 Interacting and Noninteracting Processes 88

5.5 State–Space and Transfer Function Matrix Models 90

5.6 Multiple–Input, Multiple–Output (MIMO) Processes 93

6. Development of Empirical Models from Process Data 102

6.1 Model Development Using Linear or Nonlinear Regression 103

6.2 Fitting First– and Second–Order Models Using Step Tests 107

6.3 Neural Network Models 112

6.4 Development of Discrete–Time Dynamic Models 113

6.5 Identifying Discrete–Time Models from Experimental Data 115

PART THREE FEEDBACK AND FEEDFORWARD CONTROL

7. Feedback Controllers 124

7.1 Introduction 124

7.2 Basic Control Modes 126

7.3 Features of PID Controllers 131

7.4 On–Off Controllers 134

7.5 Typical Responses of Feedback Control Systems 134

7.6 Digital Versions of PID Controllers 135

8. Control System Instrumentation 141

8.1 Sensors, Transmitters, and Transducers 142

8.2 Final Control Elements 147

8.3 Signal Transmission and Digital Communication 153

8.4 Accuracy in Instrumentation 154

9. Process Safety and Process Control 160

9.1 Layers of Protection 161

9.2 Alarm Management 165

9.3 Abnormal Event Detection 169

9.4 Risk Assessment 171

10. Dynamic Behavior and Stability of Closed–Loop Control Systems 176

10.1 Block Diagram Representation 176

10.2 Closed–Loop Transfer Functions 179

10.3 Closed–Loop Responses of Simple Control Systems 182

10.4 Stability of Closed–Loop Control Systems 188

10.5 Root Locus Diagrams 194

11. PID Controller Design, Tuning, and Troubleshooting 204

11.1 Performance Criteria for Closed–Loop Systems 204

11.2 Model–Based Design Methods 206

11.3 Controller Tuning Relations 211

11.4 Controllers with Two Degrees of Freedom 216

11.5 On–Line Controller Tuning 217

11.6 Guidelines for Common Control Loops 223

11.7 Troubleshooting Control Loops 225

12. Control Strategies at the Process Unit Level 232

12.1 Degrees of Freedom Analysis for Process Control 232

12.2 Selection of Controlled, Manipulated, and Measured Variables 234

12.3 Applications 238

13. Frequency Response Analysis and Control System Design 248

13.1 Sinusoidal Forcing of a First–Order Process 248

13.2 Sinusoidal Forcing of an nth–Order Process 249

13.3 Bode Diagrams 251

13.4 Frequency Response Characteristics of Feedback Controllers 255

13.5 Nyquist Diagrams 260

13.6 Bode Stability Criterion 260

13.7 Gain and Phase Margins 264

14. Feedforward and Ratio Control 271

14.1 Introduction to Feedforward Control 271

14.2 Ratio Control 273

14.3 Feedforward Controller Design Based on Steady–State Models 275

14.4 Feedforward Controller Design Based on Dynamic Models 277

14.5 The Relationship Between the Steady–State and Dynamic Design Methods 281

14.6 Configurations for Feedforward–Feedback Control 282

14.7 Tuning Feedforward Controllers 282

PART FOUR ADVANCED PROCESS CONTROL

15. Enhanced Single–Loop Control Strategies 288

15.1 Cascade Control 288

15.2 Time–Delay Compensation 293

15.3 Inferential Control 296

15.4 Selective Control/Override Systems 297

15.5 Nonlinear Control Systems 300

15.6 Adaptive Control Systems 307

16. Multiloop and Multivariable Control 317

16.1 Process Interactions and Control Loop Interactions 317

16.2 Pairing of Controlled and Manipulated Variables 323

16.3 Singular Value Analysis 330

16.4 Tuning of Multiloop PID Control Systems 334

16.5 Decoupling and Multivariable Control Strategies 334

16.6 Strategies for Reducing Control Loop Interactions 336

17. Digital Sampling, Filtering, and Control 344

17.1 Sampling and Signal Reconstruction 344

17.2 Signal Processing and Data Filtering 347

17.3 z–Transform Analysis for Digital Control 352

17.4 Tuning of Digital PID Controllers 358

17.5 Direct Synthesis for Design of Digital Controllers 360

17.6 Minimum Variance Control 364

18. Batch Process Control 371

18.1 Batch Control Systems 373

18.2 Sequential and Logic Control 374

18.3 Control During the Batch 380

18.4 Run–to–Run Control 386

18.5 Batch Production Management 387

Chapters 19 through 23 are  online in Instructors Rsources

19. Real–Time Optimization 395

19.1 Basic Requirements in Real–Time Optimization 396

19.2 The Formulation and Solution of RTO Problems 399

19.3 Unconstrained and Constrained Optimization 401

19.4 Linear Programming 404

19.5 Quadratic and Nonlinear Programming 408

20. Model Predictive Control 414

20.1 Overview of Model Predictive Control 414

20.2 Predictions for SISO Models 416

20.3 Predictions for MIMO Models 421

20.4 Model Predictive Control Calculations 423

20.5 Set–Point Calculations 427

20.6 Selection of Design and Tuning Parameters 429

20.7 Implementation of MPC 434

21. Process Monitoring 439

21.1 Traditional Monitoring Techniques 440

21.2 Quality Control Charts 441

21.3 Extensions of Statistical Process Control 447

21.4 Multivariate Statistical Techniques 449

21.5 Control Performance Monitoring 451

PART FIVE APPLICATIONS TO BIOLOGICAL SYSTEMS

22. Biosystems Control Design 456

22.1 Process Modeling and Control in Pharmaceutical Operations 456

22.2 Process Modeling and Control for Drug Delivery 462

23. Dynamics and Control of Biological Systems 470

24.1 Systems Biology 470

24.2 Gene Regulatory Control 472

24.3 Signal Transduction Networks 476

Appendix A: Laplace Transforms A–1

A.1 The Laplace Transform of Representative Functions A–1

A.2 Solution of Differential Equations by Laplace Transform Techniques A–5

A.3 Partial Fraction Expansion A–7

A.4 Other Laplace Transform Properties A–10

A.5 A Transient Response Example A–13

Appendix B: Digital Process Control Systems: Hardware and Software A–21

B.1 Distributed Digital Control Systems A–22

B.2 Analog and Digital Signals and Data Transfer A–22

B.3 Microprocessors and Digital Hardware in Process Control A–24

B.4 Software Organization A–27

Appendix C: Review of Thermodynamic Concepts for Conservation Equations A–34

C.1 Single–Component Systems A–34

C.2 Multicomponent Systems A–35

Appendix D: Control Simulation Software A–36

D.1 MATLAB Operations and Equation Solving A–36

D.2 Computer Simulation with Simulink A–38

D.3 Computer Simulation with LabVIEW A–40

Appendix E: Process Control Modules A–43

E.1. Introduction A–43

E.2. Module Organization A–43

E.3. Hardware and Software Requirements A–44

E.4. Installation A–44

E.5. Running the Software A–44

Appendices F through K are online in Instructors Resources

Appendix F: Introduction to Plantwide Control A–45

F.1 Plantwide Control Issues A–45

F.2 Hypothetical Plant for Plantwide Control Studies A–47

F.3 Internal Feedback of Material and Energy A–51

F.4 Interaction of Plant Design and Control System Design A–59

Appendix G: Plantwide Control System Design A–63

G.1 Procedures for the Design of Plantwide Control Systems A–63

G.2 A Systematic Procedure for Plantwide Control System Design A–64

G.3 Case Study: The Reactor/Flash Unit Plant A–67

G.4 Effect of Control Structure on Closed–Loop Performance A–78

Appendix H: Dynamic Models and Parameters Used for Plantwide Control Chapters A–82

H.1 Energy Balance and Parameters for the Reactor/Distillation Column Model A–82

H.2 Core Reactor/Flash Unit Model and Parameters A–82

Appendix I: Instrumentation Symbols A–88

Appendix J: Review of Basic Concepts from Probability and Statistics A–90

J.1 Probability Concepts A–90

J.2 Means and Variances A–91

J.3 Standard Normal Distribution A–91

J.4 Error Analysis A–92

Appendix K: Contour Mapping and the Principle of the Argument A–93

K.1 Development of the Nyquist Stability Criterion A–93

Index I–1

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Dale E. Seborg
Thomas F. Edgar
Duncan A. Mellichamp
Francis J. Doyle III
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