The new 4th edition of Seborg’s Process Dynamics Control provides full topical coverage for process control courses in the chemical engineering curriculum, emphasizing how process control and its related fields of process modeling and optimization are essential to the development of high-value products. A principal objective of this new edition is to describe modern techniques for control processes, with an emphasis on complex systems necessary to the development, design, and operation of modern processing plants. Control process instructors can cover the basic material while also having the flexibility to include advanced topics.

Table of Contents:
PART ONE INTRODUCTION TO PROCESS CONTROL 1. Introduction to Process Control 1 1.1 Representative Process Control Problems 2 1.2 Illustrative Example—A Blending Process 4 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 14 2.1 The Rationale for Dynamic Process Models 14 2.2 General Modeling Principles 16 2.3 Degrees of Freedom Analysis 19 2.4 Dynamic Models of Representative Processes 21 2.5 Process Dynamics and Mathematical Models 30 PART TWO DYNAMIC BEHAVIOR OF PROCESSES 3. Laplace Transforms 38 3.1 Laplace Transforms of Representative Functions 39 3.2 Solution of Differential Equations by Laplace Transform Techniques 42 3.3 Partial Fraction Expansion 43 3.4 Other Laplace Transform Properties 45 3.5 A Transient Response Example 47 3.6 Software for Solving Symbolic Mathematical Problems 49 4. Transfer Function Models 54 4.1 Introduction to Transfer Function Models 54 4.2 Properties of Transfer Functions 57 4.3 Linearization of Nonlinear Models 61 5. Dynamic Behavior of First-Order and Second-Order Processes 68 5.1 Standard Process Inputs 69 5.2 Response of First-Order Processes 70 5.3 Response of Integrating Processes 73 5.4 Response of Second-Order Processes 75 6. Dynamic Response Characteristics of More Complicated Processes 86 6.1 Poles and Zeros and Their Effect on Process Response 86 6.2 Processes with Time Delays 89 6.3 Approximation of Higher-Order Transfer Functions 92 6.4 Interacting and Noninteracting Processes 94 6.5 State-Space and Transfer Function Matrix Models 95 6.6 Multiple-Input, Multiple-Output (MIMO) Processes 98 7. Development of Empirical Models from Process Data 105 7.1 Model Development Using Linear or Nonlinear Regression 106 7.2 Fitting First- and Second-Order Models Using Step Tests 109 7.3 Neural Network Models 113 7.4 Development of Discrete-Time Dynamic Models 115 7.5 Identifying Discrete-Time Models from Experimental Data 116 PART THREE FEEDBACK AND FEEDFORWARD CONTROL 8. Feedback Controllers 123 8.1 Introduction 123 8.2 Basic Control Modes 125 8.3 Features of PID Controllers 130 8.4 Digital Versions of PID Controllers 133 8.5 Typical Responses of Feedback Control Systems 135 8.6 On–Off Controllers 136 9. Control System Instrumentation 140 9.1 Sensors, Transmitters, and Transducers 141 9.2 Final Control Elements 148 9.3 Accuracy in Instrumentation 154 10. Process Safety and Process Control 160 10.1 Layers of Protection 161 10.2 Alarm Management 165 10.3 Abnormal Event Detection 169 10.4 Risk Assessment 170 11. Dynamic Behavior and Stability of Closed-Loop Control Systems 175 11.1 Block Diagram Representation 176 11.2 Closed-Loop Transfer Functions 178 11.3 Closed-Loop Responses of Simple Control Systems 181 11.4 Stability of Closed-Loop Control Systems 186 11.5 Root Locus Diagrams 191 12. PID Controller Design, Tuning, and Troubleshooting 199 12.1 Performance Criteria for Closed-Loop Systems 200 12.2 Model-Based Design Methods 201 12.3 Controller Tuning Relations 206 12.4 Controllers with Two Degrees of Freedom 213 12.5 On-Line Controller Tuning 214 12.6 Guidelines for Common Control Loops 220 12.7 Troubleshooting Control Loops 222 13. Control Strategies at the Process Unit Level 229 13.1 Degrees of Freedom Analysis for Process Control 230 13.2 Selection of Controlled, Manipulated, and Measured Variables 232 13.3 Applications 235 14. Frequency Response Analysis and Control System Design 244 14.1 Sinusoidal Forcing of a First-Order Process 244 14.2 Sinusoidal Forcing of an nth-Order Process 246 14.3 Bode Diagrams 247 14.4 Frequency Response Characteristics of Feedback Controllers 251 14.5 Nyquist Diagrams 252 14.6 Bode Stability Criterion 252 14.7 Gain and Phase Margins 256 15. Feedforward and Ratio Control 262 15.1 Introduction to Feedforward Control 263 15.2 Ratio Control 264 15.3 Feedforward Controller Design Based on Steady-State Models 266 15.4 Feedforward Controller Design Based on Dynamic Models 268 15.5 The Relationship Between the Steady-State and Dynamic Design Methods 272 15.6 Configurations for Feedforward–Feedback Control 272 15.7 Tuning Feedforward Controllers 273 PART FOUR ADVANCED PROCESS CONTROL 16. Enhanced Single-Loop Control Strategies 279 16.1 Cascade Control 279 16.2 Time-Delay Compensation 284 16.3 Inferential Control 286 16.4 Selective Control/Override Systems 287 16.5 Nonlinear Control Systems 289 16.6 Adaptive Control Systems 292 17. Digital Sampling, Filtering, and Control 300 17.1 Sampling and Signal Reconstruction 300 17.2 Signal Processing and Data Filtering 303 17.3 z-Transform Analysis for Digital Control 307 17.4 Tuning of Digital PID Controllers 313 17.5 Direct Synthesis for Design of Digital Controllers 315 17.6 Minimum Variance Control 319 18. Multiloop and Multivariable Control 326 18.1 Process Interactions and Control Loop Interactions 327 18.2 Pairing of Controlled and Manipulated Variables 331 18.3 Singular Value Analysis 338 18.4 Tuning of Multiloop PID Control Systems 341 18.5 Decoupling and Multivariable Control Strategies 342 18.6 Strategies for Reducing Control Loop Interactions 343 19. Real-Time Optimization 350 19.1 Basic Requirements in Real-Time Optimization 352 19.2 The Formulation and Solution of RTO Problems 354 19.3 Unconstrained and Constrained Optimization 356 19.4 Linear Programming 359 19.5 Quadratic and Nonlinear Programming 362 20. Model Predictive Control 368 20.1 Overview of Model Predictive Control 369 20.2 Predictions for SISO Models 370 20.3 Predictions for MIMO Models 377 20.4 Model Predictive Control Calculations 379 20.5 Set-Point Calculations 382 20.6 Selection of Design and Tuning Parameters 384 20.7 Implementation of MPC 389 21. Process Monitoring 395 21.1 Traditional Monitoring Techniques 397 21.2 Quality Control Charts 398 21.3 Extensions of Statistical Process Control 404 21.4 Multivariate Statistical Techniques 406 21.5 Control Performance Monitoring 408 22. Batch Process Control 413 22.1 Batch Control Systems 415 22.2 Sequential and Logic Control 416 22.3 Control During the Batch 421 22.4 Run-to-Run Control 426 22.5 Batch Production Management 427 PART FIVE APPLICATIONS TO BIOLOGICAL SYSTEMS 23. Biosystems Control Design 435 23.1 Process Modeling and Control in Pharmaceutical Operations 435 23.2 Process Modeling and Control for Drug Delivery 442 24. Dynamics and Control of Biological Systems 451 24.1 Systems Biology 451 24.2 Gene Regulatory Control 453 24.3 Signal Transduction Networks 457 Appendix A: Digital Process Control Systems: Hardware and Software 464 A.1 Distributed Digital Control Systems 465 A.2 Analog and Digital Signals and Data Transfer 466 A.3 Microprocessors and Digital Hardware in Process Control 467 A.4 Software Organization 470 Appendix B: Review of Thermodynamic Concepts for Conservation Equations 478 B.1 Single-Component Systems 478 B.2 Multicomponent Systems 479 Appendix C: Control Simulation Software 480 C.1 MATLAB Operations and Equation Solving 480 C.2 Computer Simulation with Simulink 482 C.3 Computer Simulation with LabVIEW 485 Appendix D: Instrumentation Symbols 487 Appendix E: Process Control Modules 489 E.1 Introduction 489 E.2 Module Organization 489 E.3 Hardware and Software Requirements 490 E.4 Installation 490 E.5 Running the Software 490 Appendix F: Review of Basic Concepts From Probability and Statistics 491 F.1 Probability Concepts 491 F.2 Means and Variances 492 F.3 Standard Normal Distribution 493 F.4 Error Analysis 493 Appendix G: Introduction to Plantwide Control (Available online at: www.wiley.com/college/seborg) Appendix H: Plantwide Control System Design (Available online at: www.wiley.com/college/seborg) Appendix I: Dynamic Models and Parameters Used for Plantwide Control Chapters (Available online at: www.wiley.com/college/seborg) Appendix J: Additional Closed-Loop Frequency Response Material (Available online at: www.wiley.com/college/seborg) Appendix K: Contour Mapping and the Principle of the Argument (Available online at: www.wiley.com/college/seborg) Appendix L: Partial Fraction Expansions for Repeated and Complex Factors (Available online at: www.wiley.com/college/seborg) Index 495