book

Process Control: Modeling, Design, and Simulation, 2nd Edition

Name: Process Control: Modeling, Design, and Simulation, 2nd Edition
Author: B. Wayne Bequette
ISBN: 9780134033846

by B. Wayne Bequette

August 2023

Intermediate to advanced

768 pages

20h 43m

English

Pearson

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Cover Page
About This eBook
Halftitle Page
Title Page
Copyright Page
Humans are born to learn
Dedication Page
Contents
Preface to the Second Edition
About the Author

Chapter 1. Introduction
1.1 Introduction1.2 Instrumentation1.3 Process Models and Dynamic Behavior1.4 Redundancy and Operability1.5 Industrial IoT and Smart Manufacturing1.6 Control Textbooks1.7 A Look Ahead1.8 SummaryReferencesStudent Exercises
Chapter 2. Fundamental Models
2.1 Background2.2 Balance Equations2.3 Material Balances2.4 Constitutive Relationships2.5 Material and Energy Balances2.6 Form of Dynamic Models2.7 Linear Models and Deviation Variables2.8 SummarySuggested ReadingStudent Exercises
Chapter 3. Dynamic Behavior
3.1 Background3.2 Linear State-Space Models3.3 Laplace Transforms3.4 Transfer Functions3.5 First-Order Behavior3.6 Integrating Behavior3.7 Second-Order Behavior3.8 SummaryReferencesStudent Exercises
Chapter 4. Dynamic Behavior: Complex Systems
4.1 Introduction4.2 Poles and Zeros4.3 Lead-Lag Behavior4.4 Processes with Deadtime4.5 Padé Approximation for Deadtime4.6 Converting State-Space Models to Transfer Functions4.7 Converting Transfer Functions to State-Space Models4.8 Matlab and Simulink4.9 SummaryStudent Exercises
Chapter 5. Empirical and Discrete-Time Models
5.1 Introduction5.2 First-Order + Deadtime5.3 Integrator + Deadtime5.4 Other Continuous Models5.5 Discrete-Time Autoregressive Models5.6 Parameter Estimation5.7 Discrete Step and Impulse Response Models5.8 Converting Continuous Models to Discrete5.9 Digital Filtering5.10 SummaryReferencesStudent ExercisesAppendix 5.1: Discretization
Chapter 6. Introduction to Feedback Control
6.1 Motivation6.2 Control Block Diagrams6.3 Closed-Loop Analysis6.4 PID Controller Algorithms6.5 Routh Stability Criterion6.6 Effect of Tuning Parameters6.7 Open-Loop Unstable Systems6.8 Simulink Block Diagrams6.9 ODEs to Solve PID Problems6.10 SummaryReferencesStudent Exercises
Chapter 7. Model-Based Control
7.1 Introduction7.2 Direct Synthesis7.3 Internal Model Control7.4 IMC-Based PID7.5 IMC-Based PID for Time-Delay Processes7.6 IMC-Based PID for Unstable Processes7.7 SummaryReferencesStudent ExercisesAppendix 7.1: SIMC-Based PID Design
Chapter 8. PID Controller Tuning
8.1 Introduction8.2 Closed-Loop Oscillation-Based Tuning8.3 Tuning Rules for First-Order + Deadtime Processes8.4 Digital Control8.5 Stability of Digital Control Systems8.6 Performance of Digital Control Systems8.7 SummaryReferencesStudent Exercises
Chapter 9. Frequency-Response Analysis
9.1 Motivation9.2 Bode and Nyquist Plots9.3 Effect of Process Parameters on Bode and Nyquist Plots9.4 Closed-Loop Stability9.5 Bode and Nyquist Stability9.6 Robustness9.7 Matlab Control Toolbox: Bode and Nyquist Functions9.8 SummaryReferenceStudent Exercises
Chapter 10. Cascade and Feedforward Control
10.1 Background10.2 Introduction to Cascade Control10.3 Cascade-Control Analysis10.4 Cascade-Control Design10.5 Feedforward Control10.6 Feedforward Controller Design10.7 Summary of Feedforward Control10.8 Combined Feedforward and Cascade10.9 SummaryReferencesStudent Exercises
Chapter 11. PID Enhancements
11.1 Background11.2 Antireset Windup11.3 Autotuning Techniques11.4 Nonlinear PID Control11.5 Controller Parameter (Gain) Scheduling11.6 Measurement/Actuator Selection11.7 Implementing PID Enhancements in Simulink11.8 SummaryReferencesStudent Exercises
Chapter 12. Ratio, Selective, and Split-Range Control
12.1 Motivation12.2 Ratio Control12.3 Selective and Override Control12.4 Split-Range Control12.5 Simulink Functions12.6 SummaryReferencesStudent Exercises
Chapter 13. Control-Loop Interaction
13.1 Introduction13.2 Motivation13.3 The General Pairing Problem13.4 The Relative Gain Array13.5 Properties and Application of the RGA13.6 Return to the Motivating Example13.7 RGA and Sensitivity13.8 Using the RGA to Determine Variable Pairings13.9 Matlab RGA Function File13.10 SummaryReferencesStudent ExercisesAppendix 13.1: Derivation of the Relative Gain for an n-Input–n-Output SystemAppendix 13.2: m-File to Calculate the RGA
Chapter 14. Multivariable Control
14.1 Background14.2 Zeros and Performance Limitations14.3 Scaling Considerations14.4 Directional Sensitivity and Operability14.5 Block-Diagram Analysis14.6 Decoupling14.7 Matlab tzero, svd14.8 SummaryReferencesStudent ExercisesAppendix 14.1
Chapter 15. Plantwide Control
15.1 Background15.2 Steady-State and Dynamic Effects of Recycle15.3 Unit Operations Not Previously Covered15.4 The Control and Optimization Hierarchy15.5 Further Plantwide Control Examples15.6 Simulations15.7 Startup, Safety, and the Human-in-the-Loop15.8 SummaryReferencesStudent ExercisesAppendix 15.1
Chapter 16. Model Predictive Control
16.1 Motivation16.2 Optimization Problem16.3 Dynamic Matrix Control16.4 Constraints and Multivariable Systems16.5 Other MPC Methods16.6 Matlab16.7 SummaryReferences and Relevant LiteratureStudent ExercisesAppendix 16.1: Derivation of the Step Response FormulationAppendix 16.2: Derivation of the Least-Squares Solution for Control MovesAppendix 16.3: State Space Formulation for MPC
Chapter 17. Summary
17.1 Overview of Topics Covered in This Textbook17.2 Process Engineering in Practice17.3 Suggested Further ReadingStudent Exercises
Module 1. Introduction to Matlab
M1.1 BackgroundM1.2 Matrix OperationsM1.3 The Matlab WorkspaceM1.4 Complex VariablesM1.5 PlottingM1.6 More Matrix StuffM1.7 for LoopsM1.8 m-FilesM1.9 Summary of Commonly Used CommandsM1.10 Frequently Used Matlab FunctionsAdditional Exercises
Module 2. Introduction to Simulink
M2.1 BackgroundM2.2 Open-Loop SimulationsM2.3 Feedback-Control SimulationsM2.4 SummaryAdditional Exercises
Module 3. Ordinary Differential Equations
M3.1 Matlab ode—BasicM3.2 Matlab ode—OptionsM3.3 Simulink sfunM3.4 SummaryAdditional Exercises
Module 4. Matlab LTI Models
M4.1 Forming Continuous-Time ModelsM4.2 Forming Discrete-Time ModelsM4.3 Converting Continuous Models to DiscreteM4.4 Converting Discrete Models to ContinuousM4.5 Step and Impulse ResponsesM4.6 SummaryAdditional Exercises
Module 5. Isothermal Chemical Reactor
M5.1 BackgroundM5.2 ModelM5.3 Steady-State and Dynamic BehaviorM5.4 Closed-Loop ControlReferenceAdditional Exercises
Module 6. Biochemical Reactors
M6.1 BackgroundM6.2 Steady-State and Dynamic BehaviorM6.3 Stable Steady-State Operating PointM6.4 Unstable Steady-State Operating PointM6.5 Simulink Model FileReferenceAdditional Exercises
Module 7. CSTR
M7.1 BackgroundM7.2 Simplified Modeling EquationsM7.3 Example Chemical Process—Propylene Glycol ProductionM7.4 Effect of Reactor ScaleM7.5 For Further Study: Detailed ModelM7.6 Other ConsiderationsM7.7 SummaryReferencesAdditional ExercisesAppendix M7.1
Module 8. Steam Drum Level
M8.1 BackgroundM8.2 Process ModelM8.3 Feedback Controller DesignM8.4 Feedforward Controller DesignM8.5 Three-Mode Level ControlAppendix M8.1: Simulink Diagram for Feedforward/Feedback Control of Steam Drum LevelAppendix M8.2: Simulink Diagram for Three-Mode Control of Steam Drum Level
Module 9. Surge Vessel Level Control
M9.1 BackgroundM9.2 Process ModelM9.3 Controller DesignM9.4 Numerical ExampleM9.5 SummaryReferenceAdditional ExercisesAppendix M9.1: The Simulink Block Diagram
Module 10. Batch Reactor
M10.1 BackgroundM10.2 Batch Model 1: Jacket Temperature ManipulatedM10.3 Batch Model 2: Jacket Inlet Temperature ManipulatedM10.4 Batch Model 3: Cascade ControlM10.5 SummaryReferenceAdditional Exercises
Module 11. Biomedical Systems
M11.1 OverviewM11.2 Pharmacokinetic ModelsM11.3 Intravenous Delivery of Anesthetic DrugsM11.4 Blood Glucose Control in ICU PatientsM11.5 Critical Care PatientsM11.6 SummaryReferencesAdditional Exercises
Module 12. Automated Insulin Delivery
M12.1 Background: Physiology of Blood Glucose RegulationM12.2 Type 1 DiabetesM12.3 Closed-Loop Components and DiagramM12.4 Simulation ModelM12.5 Open-Loop Responses to Meal and InsulinM12.6 Closed-Loop ResponsesM12.7 SummaryReferencesSuggested Further StudyAdditional Exercises
Module 13. Distillation Control
M13.1 Description of Distillation ControlM13.2 Open-Loop BehaviorM13.3 SISO ControlM13.4 RGA AnalysisM13.5 Multiple SISO ControllersM13.6 Singular Value AnalysisM13.7 Nonlinear EffectsM13.8 Other Issues in Distillation Column ControlM13.9 SummaryReferencesAdditional Exercises
Module 14. Case Study Problems
M14.1 BackgroundM14.2 Reactive Ion EtcherM14.3 Rotary Lime Kiln Temperature ControlM14.4 Fluidized Catalytic Cracking UnitM14.5 Anaerobic Sludge DigesterM14.6 Suggested Case Study ScheduleM14.7 SummaryAdditional Exercises
Module 15. Process Monitoring
M15.1 Concise Review of ProbabilityM15.2 Statistical Process ControlM15.3 Characteristic Process NoiseM15.4 Filtering and SmoothingM15.5 Data ReconciliationM15.6 Gross Error DetectionM15.7 SummaryReferencesAdditional ExercisesAppendix M15.1
Module 16. Safety
M16.1 OverviewM16.2 Chemical Process DisastersM16.3 Aircraft DisastersM16.4 Fault Detection Algorithms and Safety ScienceM16.5 SummaryReferencesAdditional Exercises
Index
Code Snippets

Content preview from Process Control: Modeling, Design, and Simulation, 2nd Edition

Chapter 5 Empirical and Discrete-Time Models

The previous three chapters focused on (i) the development of fundamental models based on material and energy balances and (ii) understanding dynamic behavior, with an emphasis on linear systems. In this chapter, we discuss the development of empirical models, that is, developing models based on plant tests. For continuous control-system design (most of the focus of this text), a study of Sections 5.1, 5.2, and 5.3 will be sufficient. The discrete models developed in Sections 5.4 and 5.5 will be useful when model predictive control (MPC) techniques are presented in Chapter 16, “Model Predictive Control,” and when digital control is studied in Module 16, “Digital Control.”

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Process Control: Modeling, Design, and Simulation, 2nd Edition

by B. Wayne Bequette

Chapter 5

Empirical and Discrete-Time Models

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