Book description
Master Process Control Hands On, through Updated Practical Examples and MATLAB® Simulations
Process Control: Modeling, Design, and Simulation, Second Edition, is a complete introduction to process control and has been fully updated, integrating current software tools to enable professionals and students to master critical techniques hands on through simulations based on modern versions of MATLAB. This revised edition teaches the field's most important techniques, behaviors, and control problems with even more practical examples and exercises. Wide-ranging enhancements include safety considerations, an expanded discussion of digital control, additional process examples, and updates throughout for newer versions of MATLAB and SIMULINK.
Fundamentals of process control and instrumentation, including objectives, variables, block diagrams, and process flowsheets
Methodologies for developing dynamic models of chemical processes, including compartmental models
Dynamic behavior of linear systems: state-space models, transfer function-based models (including conversion to state space), and more
Empirical and discrete-time models, including relationships among types of discrete models
Feedback control; proportional, integral, and derivative (PID) controllers; and closed-loop stability analysis
Frequency response analysis techniques for evaluating the robustness of control systems
Improving control loop performance: internal model control (IMC), automatic tuning, gain scheduling, and enhanced disturbance rejection
Split-range, selective, and override strategies for switching among inputs or outputs
Control loop interactions and multivariable controllers
An introduction to model predictive control (MPC), with a new discrete state-space model derivation exercise
Bequette walks step by step through developing control instrumentation diagrams for an entire chemical process, reviewing common control strategies for individual unit operations, then discussing strategies for integrated systems. This edition also includes 16 learning modules demonstrating how to use MATLAB and SIMULINK to solve many key control problems, including new modules on process monitoring and safety, as well as a detailed new study of artificial pancreas systems for Type 1 diabetes.
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Table of contents
- Cover Page
- About This eBook
- Halftitle Page
- Title Page
- Copyright Page
- Pearson’s Commitment to Diversity, Equity, and Inclusion
- Dedication Page
- Contents
- Preface to the Second Edition
- About the Author
- Chapter 1. Introduction
- Chapter 2. Fundamental Models
- Chapter 3. Dynamic Behavior
- Chapter 4. Dynamic Behavior: Complex Systems
-
Chapter 5. Empirical and Discrete-Time Models
- 5.1 Introduction
- 5.2 First-Order + Deadtime
- 5.3 Integrator + Deadtime
- 5.4 Other Continuous Models
- 5.5 Discrete-Time Autoregressive Models
- 5.6 Parameter Estimation
- 5.7 Discrete Step and Impulse Response Models
- 5.8 Converting Continuous Models to Discrete
- 5.9 Digital Filtering
- 5.10 Summary
- References
- Student Exercises
- Appendix 5.1: Discretization
- Chapter 6. Introduction to Feedback Control
- Chapter 7. Model-Based Control
- Chapter 8. PID Controller Tuning
- Chapter 9. Frequency-Response Analysis
- Chapter 10. Cascade and Feedforward Control
- Chapter 11. PID Enhancements
- Chapter 12. Ratio, Selective, and Split-Range Control
-
Chapter 13. Control-Loop Interaction
- 13.1 Introduction
- 13.2 Motivation
- 13.3 The General Pairing Problem
- 13.4 The Relative Gain Array
- 13.5 Properties and Application of the RGA
- 13.6 Return to the Motivating Example
- 13.7 RGA and Sensitivity
- 13.8 Using the RGA to Determine Variable Pairings
- 13.9 Matlab RGA Function File
- 13.10 Summary
- References
- Student Exercises
- Appendix 13.1: Derivation of the Relative Gain for an n-Input–n-Output System
- Appendix 13.2: m-File to Calculate the RGA
- Chapter 14. Multivariable Control
-
Chapter 15. Plantwide Control
- 15.1 Background
- 15.2 Steady-State and Dynamic Effects of Recycle
- 15.3 Unit Operations Not Previously Covered
- 15.4 The Control and Optimization Hierarchy
- 15.5 Further Plantwide Control Examples
- 15.6 Simulations
- 15.7 Startup, Safety, and the Human-in-the-Loop
- 15.8 Summary
- References
- Student Exercises
- Appendix 15.1
-
Chapter 16. Model Predictive Control
- 16.1 Motivation
- 16.2 Optimization Problem
- 16.3 Dynamic Matrix Control
- 16.4 Constraints and Multivariable Systems
- 16.5 Other MPC Methods
- 16.6 Matlab
- 16.7 Summary
- References and Relevant Literature
- Student Exercises
- Appendix 16.1: Derivation of the Step Response Formulation
- Appendix 16.2: Derivation of the Least-Squares Solution for Control Moves
- Appendix 16.3: State Space Formulation for MPC
- Chapter 17. Summary
- Module 1. Introduction to Matlab
- Module 2. Introduction to Simulink
- Module 3. Ordinary Differential Equations
- Module 4. Matlab LTI Models
- Module 5. Isothermal Chemical Reactor
- Module 6. Biochemical Reactors
- Module 7. CSTR
- Module 8. Steam Drum Level
- Module 9. Surge Vessel Level Control
- Module 10. Batch Reactor
- Module 11. Biomedical Systems
- Module 12. Automated Insulin Delivery
- Module 13. Distillation Control
- Module 14. Case Study Problems
- Module 15. Process Monitoring
- Module 16. Safety
- Index
- Code Snippets
Product information
- Title: Process Control: Modeling, Design, and Simulation, 2nd Edition
- Author(s):
- Release date: August 2023
- Publisher(s): Pearson
- ISBN: 9780134033846
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