Book description
Master process control hands on, through practical examples and MATLAB® simulations
This is the first complete introduction to process control that fully integrates software tools—enabling professionals and students to master critical techniques hands on, through computer simulations based on the popular MATLAB environment. Process Control: Modeling, Design, and Simulation teaches the field's most important techniques, behaviors, and control problems through practical examples, supplemented by extensive exercises—with detailed derivations, relevant software files, and additional techniques available on a companion Web site. Coverage includes:
Fundamentals of process control and instrumentation, including objectives, variables, and block diagrams
Methodologies for developing dynamic models of chemical processes
Dynamic behavior of linear systems: state space models, transfer functionbased
models, and more
Feedback control; proportional, integral, and derivative (PID) controllers; and closedloop 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 enhancements to improve disturbance rejection
Splitrange, selective, and override strategies for switching among inputs or outputs
Control loop interactions and multivariable controllers
An introduction to model predictive control (MPC)
Bequette walks step by step through the development of control instrumentation diagrams for an entire chemical process, reviewing common control strategies for individual unit operations, then discussing strategies for integrated systems. The book also includes 16 learning modules demonstrating how to use MATLAB and SIMULINK to solve several key control problems, ranging from robustness analyses to biochemical reactors, biomedical problems to multivariable control.
Table of contents
 Copyright
 PRENTICE HALL INTERNATIONAL SERIES IN THE PHYSICAL AND CHEMICAL ENGINEERING SCIENCES
 About Prentice Hall Professional Technical Reference
 Preface
 Introduction

Fundamental Models
 Background
 Balance Equations
 Material Balances
 Constitutive Relationships
 Material and Energy Balances
 Form of Dynamic Models
 Linear Models and Deviation Variables
 Summary

Suggested Reading
 Student Exercises
 Appendix 2.1: Solving Algebraic Equations
 Appendix 2.2: Integrating Ordinary Differential Equations

Dynamic Behavior
 Background
 Linear State Space Models
 Introduction to Laplace Transforms
 Transfer Functions
 FirstOrder Behavior
 Integrating System
 SecondOrder Behavior
 LeadLag Behavior
 Poles and Zeros
 Processes with Dead Time
 Padé Approximation for Dead Time
 Converting State Space Models to Transfer Functions
 MATLAB and SIMULINK
 Summary
 References
 Student Exercises
 Empirical Models
 Introduction to Feedback Control
 PID Controller Tuning
 FrequencyResponse Analysis

Internal Model Control
 Introduction to ModelBased Control
 Practical OpenLoop Controller Design
 Generalization of the OpenLoop Control Design Procedure
 Model Uncertainty and Disturbances
 Development of the IMC Structure
 IMC Background
 The IMC Structure
 The IMC Design Procedure
 Effect of Model Uncertainty and Disturbances
 Improved Disturbance Rejection Design
 Manipulated Variable Saturation
 Summary
 References
 Student Exercises
 Appendix 8.1: Derivation of ClosedLoop Relationships for IMC

The IMCBased PID Procedure
 Background
 The Equivalent Feedback Form to IMC
 IMCBased Feedback Design for DelayFree Processes
 IMCBased Feedback Design for Processes with a Time Delay
 Summary of IMCBased PID Controller Design for Stable Processes
 IMCBased PID Controller Design for Unstable Processes
 Summary
 References
 Student Exercises

Cascade and FeedForward Control
 Background
 Introduction to Cascade Control
 CascadeControl Analysis
 CascadeControl Design
 Cascade IMC
 FeedForward Control
 FeedForward Controller Design
 FeedForward Control in the IMC Structure
 Summary of FeedForward Control
 Combined FeedForward and Cascade
 Summary
 References
 Student Exercises—Cascade Control
 Student Exercises—FeedForward Control
 Student Exercises—FeedForward and Cascade
 PID Enhancements
 Ratio, Selective, and SplitRange Control

ControlLoop Interaction
 Introduction
 Motivation
 The General Pairing Problem
 The Relative Gain Array
 Properties and Application of the RGA
 Return to the Motivating Example
 RGA and Sensitivity
 Using the RGA to Determine Variable Pairings
 MATLAB RGA Function File
 Summary

References
 Student Exercises
 Appendix 13.1: Derivation of the Relative Gain for an nInput–nOutput System
 Appendix 13.2: mFile to Calculate the RGA
 Multivariable Control
 Plantwide Control

Model Predictive Control
 Motivation
 Optimization Problem
 Dynamic Matrix Control
 Constraints and Multivariable Systems
 Other MPC Methods
 Matlab
 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
 Summary
 Introduction to MATLAB
 Introduction to SIMULINK
 Ordinary Differential Equations
 MATLAB LTI Models
 Isothermal Chemical Reactor
 FirstOrder + TimeDelay Processes
 Biochemical Reactors
 CSTR
 Steam Drum Level
 Surge Vessel Level Control
 Batch Reactor
 Biomedical Systems
 Distillation Control
 Case Study Problems
 Flow Control
 Digital Control
 About the Author
Product information
 Title: Process Control: Modeling, Design, and Simulation
 Author(s):
 Release date: December 2002
 Publisher(s): Pearson
 ISBN: 0133536408
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