Process Dynamics and Control, 4ed (An Indian Adaptation)

Dale E. Seborg, Thomas F. Edgar, Duncan A. Mellichamp, and Francis J. Doyle III

ISBN: 9789354248429

700 pages

INR 879


This Indian adaptation of the fourth edition of the book, builds on the conceptual strength of the previous editions, with the focus on addition and reorganization of topics to make it a better-fit textbook for Indian Universities. It offers new and updated material on basic and advanced process control, particularly related to MATLAB® applications. Useful new key features are presentation of the entire text including solved examples and exercise problems in SI units and extensive use of MATLAB®/Simulink® to supplement standard hand-solved examples.

Preface to the Adapted Edition


Part One: Introduction to Process Control

Chapter 1 Introduction to Process Control

1.1 Need for Control Systems

1.2 Characteristics of Process Control Problems

1.3 Designing Control Systems for a Process

1.4 Classification of Process Control Strategies

1.5 Multiloop Versus Multivariable Control

1.6 Design Aspects of Control Systems


Chapter 2 Theoretical Models of Chemical Processes

2.1 Dynamic Process Models – Their Strengths and Limitations

2.2 General Modeling Principles

2.3 Degrees of Freedom Analysis

2.4 Degrees of Freedom Analysis for Process Control

2.5 Dynamic Models of Representative Processes

2.6 Solving Differential Equations using MATLAB


Part Two: Dynamic Behavior of Processes

Chapter 3 Laplace Transforms

3.1 Laplace Transforms of Representative Functions

3.2 Solution of Differential Equations by Laplace Transform Techniques

3.3 Partial Fraction Expansion (PFE)

3.4 Other Laplace Transform Properties

3.5 A Transient Response Example

3.6 Solving Laplace Transform Problems using MATLAB


Chapter 4 Transfer Function and State-Space Models

4.1 Introduction to Transfer Function Models

4.2 Properties of Transfer Functions

4.3 Linearization of Nonlinear Models

4.4 State-Space and Transfer Function Matrix Models

4.5 Poles and Zeros and Their Effect on Process Response

4.6 Converting One Form of Model to Another using MATLAB


Chapter 5 Dynamic Behavior of First-Order and Second-Order Processes

5.1 Standard Process Inputs

5.2 Zero-Order Systems (Instantaneous Processes)

5.3 First-Order Processes and Their Characteristics

5.4 Response of First-Order Processes

5.5 Response of First-Order Integrating Processes

5.6 First-Order Processes with Variable Time Constant and Gain

5.7 First-Order Processes with Numerator Dynamics

5.8 Second-Order Processes and Their Types

5.9 Response of Second-Order Processes

5.10 Second-Order Processes with Numerator Dynamics

5.11 Determining Step Response Characteristics using MATLAB


Chapter 6 Dynamic Behavior of Higher-Order Processes

6.1 Processes with Time Delays

6.2 Approximation of Higher-Order Transfer Functions

6.3 Interacting and Noninteracting Processes

6.4 Multiple-Input, Multiple-Output (MIMO) Processes

6.5 Fitting First- and Second-Order Models Using Step Tests


Part Three: Classical Feedback Control

Chapter 7 Feedback Controllers

7.1 Introduction

7.2 Basic Control Modes

7.3 Features of PID Controllers

7.4 Digital Versions of PID Controllers

7.5 Typical Responses of Feedback Control Systems

7.6 On-Off Controllers

7.7 SIMULINK Model for a Feedback Control System


Chapter 8 Control System Instrumentation

8.1 Sensors, Transmitters, and Transducers

8.2 Final Control Elements

8.3 Accuracy in Instrumentation

8.4 Piping and Instrumentation Diagrams (P&ID)


Chapter 9 Dynamic Behavior and Stability of Closed-Loop Control Systems

9.1 Block Diagram Representation

9.2 Closed-Loop Transfer Functions

9.3 Closed-Loop Responses of Simple Control Systems

9.4 Stability of Closed-Loop Control Systems

9.5 Root Locus Diagrams

9.6 Rules for Drawing Root Locus Diagram

9.7 Generating Root Locus Diagram using MATLAB


Chapter 10 Frequency Response Analysis and Control System Design

10.1 Sinusoidal Forcing of A First-order Process

10.2 Sinusoidal Forcing of an nth-Order Process

10.3 Bode Diagrams

10.4 Frequency Response Characteristics of Feedback Controllers

10.5 Nyquist Diagrams

10.6 Bode Stability Criterion

10.7 Controller Design Based on Bode Stability Criterion

10.8 Gain and Phase Margins


Chapter 11 PID Controller Design, Tuning, and Troubleshooting

11.1 Performance Criteria For Closed-Loop Systems

11.2 Model-Based Design Methods

11.3 Controller Tuning Relations

11.4 Controllers With Two Degrees of Freedom

11.5 Controller Tuning Based On Simple Performance Criterion (One-Quarter Decay Ratio)

11.6 On-Line Controller Tuning

11.7 Guidelines For Common Control Loops

11.8 Troubleshooting Control Loops


Part Four: Advanced Process Control

Chapter 12 Enhanced Single-Loop Control Strategies

12.1 Feedforward Control

12.2 Ratio Control

12.3 Cascade Control

12.4 Time-Delay Compensation

12.5 Inferential Control

12.6 Selective Control Systems

12.7 Nonlinear Control Systems

12.8 Adaptive Control Systems


Chapter 13 Digital Sampling, Filtering, and Control

13.1 Components of Digital Computer Control Loop

13.2 Continuous To Discrete Transformation

13.3 Signal Processing and Data Filtering

13.4 Discrete to Continuous Transformation

13.5 z-Transform Analysis For Digital Control

13.6 Tuning of Digital PID Controllers

13.7 Direct Synthesis for Design of Digital Controllers

13.8 Minimum Variance Control


Chapter 14 Multiloop and Multivariable Control

14.1 Process Interactions and Control Loop Interactions

14.2 Pairing of Controlled and Manipulated Variables

14.3 Singular Value Analysis

14.4 Tuning of Multiloop PID Control Systems

14.5 Decoupling and Multivariable Control Strategies

14.6 Strategies for Reducing Control Loop Interactions


Chapter 15 Model Predictive Control

15.1 Overview of Model Predictive Control

15.2 Predictions for SISO Models

15.3 Predictions for MIMO Models

15.4 Model Predictive Control Calculations

15.5 Set-Point Calculations

15.6 Selection of Design and Tuning Parameters

15.7 Implementation of MPC


Chapter 16 Development of Empirical Models from Process Data

16.1 Model Development Using Linear or Nonlinear Regression

16.2 Neural Network Models

16.3 Development of Discrete-Time Dynamic Models

16.4 Identifying Discrete-Time Models from Experimental Data


Chapter 17 Process Monitoring

17.1 Traditional Monitoring Techniques

17.2 Quality Control Charts

17.3 Extensions of Statistical Process Control

17.4 Multivariate Statistical Techniques

17.5 Control Performance Monitoring


Chapter 18 Batch Process Control

18.1 Batch Control Systems

18.2 Sequential and Logic Control

18.3 Control During the Batch

18.4 Run-to-Run Control

18.5 Batch Production Management


Chapter 19 Digital Process Control Systems: Hardware and Software

19.1 Distributed Digital Control Systems

19.2 Analog and Digital Signals and Data Transfer

19.3 Microprocessors and Digital Hardware in Process Control

19.4 Software Organization





Multiple Choice Questions

Answer Key


Appendix A: Review of Thermodynamic Concepts for Conservation Equations

A.1 Single-Component Systems

A.2 Multicomponent Systems


Appendix B: Control Simulation Software

B.1 MATLAB Operations and Equation Solving

B.1.1 Matrix Operations

B.1.2 Solution of Algebraic Linear or Nonlinear Equations

B.1.3 m-files

B.1.4 Functions and Scripts

B.1.5 Solving a System of Differential Equations

B.1.6 Plots

B.1.7 MATLAB Toolboxes

B.2 Computer Simulation with Simulink

B.3 Computer Simulation with LabVIEW


Appendix C: Process Control Modules

C.1 Introduction

C.2 Module Organization

C.3 Hardware and Software Requirements

C.4 Installation

C.5 Running the Software


Appendix D: Review of Basic Concepts From Probability and Statistics

D.1 Probability Concepts

D.2 Means and Variances

D.2.1 Means and Variances for Probability Distributions

D.2.2 Means and Variances for Experimental Data

D.3 Standard Normal Distribution

D.4 Error Analysis


Appendix E: Process Safety and Process Control

E.1 Layers of Protection

E.1.1 The Role of the Basic Process Control System

E.1.2 Process Alarms

E.1.3 Safety Instrumented System (SIS)

E.1.4 Interlocks and Emergency Shutdown Systems

E.2 Alarm Management

E.2.1 Alarm Guidelines

E.2.2 Alarm Rationalization

E.3 Abnormal Event Detection

E.3.1 Fault Detection Based on Sensor and Signal Analysis

E.3.2 Model-Based Methods

E.3.3 Knowledge-Based Methods

E.4 Risk Assessment

E.4.1 Reliability Concepts

E.4.2 Overall Failure Rates

E.4.3 Fault and Event Tree Analysis


Appendix F: Real-Time Optimization

F.1 Basic Requirements in Real-Time Optimization

F.1.1 Implementation of RTO in Computer Control

F.1.2 Planning and Scheduling

F.2 The Formulation and Solution of RTO Problems

F.3 Unconstrained and Constrained Optimization

F.3.1 Single-Variable Optimization

F.3.2 Multivariable Optimization

F.4 Linear Programming

F.4.1 Linear Programming Concepts

F.5 Quadratic and Nonlinear Programming

F.5.1 Quadratic Programming

F.5.2 Nonlinear Programming Algorithms and Software


Appendix G: Biosystems Control Design

G.1 Process Modeling and Control in Pharmaceutical Operations

G.1.1 Bioreactors

G.1.2 Crystallizers

G.1.3 Granulation

G.2 Process Modeling and Control for Drug Delivery

G.2.1 Type 1 Diabetes

G.2.2 Blood Pressure Regulation

G.2.3 Cancer Treatment

G.2.4 Controlled Treatment for HIV/AIDS

G.2.5 Cardiac-Assist Devices

G.2.6 Additional Medical Opportunities for Process Control


Appendix H: Dynamics and Control of Biological Systems

H.1 Systems Biology

H.2 Gene Regulatory Control

H.2.1 Circadian Clock Network

H.3 Signal Transduction Networks

H.3.1 Chemotaxis

H.3.2 Insulin-Mediated Glucose Uptake

H.3.3 Simple Phosphorylation Transduction Cascade


Appendix I*: Introduction to Plantwide Control

Appendix J*: Plantwide Control System Design

Appendix K*: Dynamic Models and Parameters Used for Plantwide Control Chapters

Appendix L*: Additional Closed-Loop Frequency Response Material

Appendix M*: Contour Mapping and the Principle of the Argument

Appendix N*: Partial Fraction Expansions for Repeated and Complex Factors




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