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.
PART ONE: INTRODUCTION TO PROCESS CONTROL.
1. Introduction to Process Control.
1.1 Representative Process Control Problems.
1.2 Illustrative Example.
1.3 Classification of Process Control Strategies.
1.4 A More Complicated Example--A Distillation Column.
1.5 The Hierarchy of Process Control Activities.
1.6 An Overview of Control System Design.
2. Theoretical Models of Chemical Processes.
2.1 The Rationale for Process Modeling.
2.2 General Modeling Principles.
2.3 Degrees of Freedom Analysis.
2.4 Dynamic Models of Representative Processes.
2.5 Solution of Dynamic Models and the Use of Digital Simulators.
PART TWO: DYNAMIC BEHAVIOR OF PROCESSES.
3. Laplace Transforms.
3.1 The Laplace Transform of Representative Functions.
3.2 Solution of Differential Equations by Laplace Transform Techniques.
3.3 Partial Fraction Expansion.
3.4 Other Laplace Transform Properties.
3.5 A Transient Response Example.
4. Transfer Function and State-Space Models.
4.1 Illustrative Example: A Continuous Blending System.
4.2 Transfer Functions of Complicated Models.
4.3 Properties of Transfer Functions.
4.3 Linearization of Nonlinear Models.
5. Dynamic Behavior of First-Order and Second-Order Processes.
5.1 Standard Process Inputs.
5.2 Response of First-Order Processes.
5.3 Response of Integrating Processes.
5.4 Response of Second-Order Processes.
6. Dynamic Response Characteristics of More Complicated Processes.
6.1 Poles and Zeros and Their Effect on Process Response.
6.2 Processes with Time Delays.
6.3 Approximation of Higher-Order Transfer Functions.
6.4 Interacting and Noninteracting Processes.
6.5 State-Space and Transfer Function Matrix Models.
6.6 Multiple-Input, Multiple-Output (MIMO) Processes.
7. Development of Empirical Dynamic Models from Process Data.
7.1 Model Development Using Linear or Nonlinear Regression.
7.2 Methods for Fitting First-Order and Second-Order Models Using Step Tests.
7.3 Neural Network Models. Development of Discrete-Time Dynamic Models. Identifying Discrete-Time Models from Experimental Data.
PART THREE: CONTROL SYSTEM DESIGN ANALYSIS.
8. Feedback Controllers.
8.2 Basic Control Modes.
8.3 Features of PID Controllers.
8.4 On-Off Controllers.
8.5 Typical Responses of Feedback Control Systems.
8.6 Digital Versions of PID Controllers.
9. Control System Instrumentation.
9.1 Sensors, Transmitters, and Transducers.
9.2 Final Control Elements.
9.3 Signal Transmission and Digital Communication.
9.4 Accuracy in Instrumentation.
10. Process Safety and Process Control.
10.1 Layers of Protection
10.2 Alarm Management
10.3 Abnormal Event Detection
10.4 Risk Assessment
11. Dynamic Behavior and Stability of Closed-Loop Control Systems.
11.1 Block Diagram Representation.
11.2 Closed-Loop Transfer Functions.
11.3 Closed Loop Responses of Simple Control Systems.
11.4 Stability Criteria.
11.5 Pole-Zero Diagrams.
12. PID Controller Design, Tuning, and Troubleshooting.
12.2 The Influence of Process Design on Process Control.
12.3 Model-Based Design Methods.
12.4 Controller Tuning Relations.
12.5 On-Line Controller Tuning.
12.6 Guidelines for Common Control Loops.
12.7 Troubleshooting Control Loops.
13. Control at the Process Unit Level.
13.1 Degrees of Freedom for Process Control
13.2 Selection of Controlled, Manipulated, and Measured Variables
13.3 Case Studies.
14. Frequency Response Analysis and Control System Design.
14.1 Sinusoidal Forcing of a First-Order Process.
14.2 Sinusoidal Forcing of an nth-Order Process.
14.3 Bode Diagrams.
14.4 Frequency Response Characteristics of Feedback Controllers.
14.5 Bode Stability Criterion.
14.6 Gain and Phase Margins.
15. Feedforward and Ratio Control.
15.1 Introduction to Feedforward Control.
15.2 Ratio Control.
15.3 Feedforward Controller Design Based on Steady-State Models.
15.4 Controller Design Based on Dynamic Models.
15.5 The Relationship Between the Steady-State and Dynamic Design Methods.
15.6 Configurations for Feedforward-Feedback Control.
15.7 Tuning Feedforward Controllers.
PART FOUR: ADVANCED PROCESS CONTROL.
16. Enhanced Single-Loop Control Strategies.
16.1 Cascade Control.
16.2 Time-Delay Compensation.
16.3 Inferential Control.
16.4 Selective Control/Override Systems.
16.5 Nonlinear Control Systems.
16.6 Adaptive Control Systems.
17. Digital Sampling, Filtering, and Control.
17.1 Sampling and Signal Reconstruction.
17.2 Signal Processing and Data Filtering.
17.3 z-Transform Analysis for Digital Control.
17.4 Digital PID and Related Controllers.
17.5 Direct Synthesis for Design of Digital Controllers.
17.6 Minimum Variance Control.
18. Multiloop and Multivariable Control.
18.1 Process Interactions and Control Loop Interactions.
18.2 Pairing of Controlled and Manipulated Variables.
18.3 Singular Value Analysis.
18.4 Tuning of Multiloop PID Control Systems.
18.5 Decoupling and Multivariable Control Strategies.
18.6 Strategies for Reducing Control Loop Interactions.
19. Real-Time Optimization.
19.1 Basic Requirements in Real-Time Optimization.
19.2 The Formulation and Solution of RTO Problems.
19.3 Unconstrained Optimization.
19.4 Linear Programming.
19.5 Quadratic Programming/Nonlinear Programming.
20. Model Predictive Control.
20.1 Overview of Model Predictive Control.
20.2 Predictions for SISO Models.
20.3 Predictions for MIMO Models.
20.4 Model Predictive Control Calculations.
20.5 Set-Point Calculations.
20.6 Selection of Design and Tuning Parameters.
20.7 Implementation of MPC.
21. Process Monitoring.
21.1 Traditional Monitoring Techniques.
21.2 Quality Control Charts.
21.3 Extensions of Statistical Process Control.
21.4 Multivariate Statistical Techniques.
21.5 Control Performance Monitoring.
22. Batch Process Control.
22.1 Batch Control Systems.
22.2 Sequential and Logic Control.
22.3 During the Batch Control.
PART FIVE: APPLICATIONS TO BIOLOGICAL SYSTEMS.
23. Biosystems Control Design.
24.Dynamics and Control of Biological Systems.
Appendix A: Digital Process Control Systems: Hardware and Software.
Appendix B: Review of Thermodynamics Concepts for Conservation Equations.
Appendix C: Control Simulation Software.
Appendix D: Instrumentation Symbols.
Appendix E: Process Control Modules.
Appendix F: Review of Basic Concepts from Probability and Statistics.