Fundamental Process Control - 1st Edition - ISBN: 9780409900828, 9781483162379

Fundamental Process Control

1st Edition

Butterworths Series in Chemical Engineering

Authors: David M. Prett Carlos E. García
eBook ISBN: 9781483162379
Imprint: Butterworth-Heinemann
Published Date: 12th September 1988
Page Count: 262
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Fundamental Process Control focuses on the fundamental nature of process control, which includes an extensive discussion on control methodologies. The first seven chapters are devoted to the development of a complete control problem formulation that contains all the elements of practical importance. Due to the novelty of these ideas, no rigorous mathematical proofs yet exist for the assertions made, although they have been verified through simulation and experience in practice. The concepts discussed in Chapters 8 and 9 contain ideas for future developments in process control that will trigger the imagination of researchers in the fields covered. This book requires a thorough grounding in both classical and modern control theory in order to grasp the material presented. This book is therefore not for casual readers, but rather is directed at those who are currently, or those who desire to develop into, control design experts.
Within the academic community, this book is ideal for the graduate level and for those academics pursuing fundamental research topics in process control.

Table of Contents



1 Real Issues in Process Control: An Introduction

1.1 Control, Process Economics and Constraints

1.2 Design and Maintenance Costs

1.3 Technology Transfer

2 The Fundamental Control Problem Formulation

2.1 Performance Criteria for Process Control

2.1.1 The Surge Level Control Problem

2.1.2 A Semi-Batch Reactor Control Problem

2.2 Process Representation for Process Control

2.3 Summary: Elements of the Fundamental Control Problem

3 A Process Control Example Problem: Heavy Oil Fractionator

3.1 Process Representation

3.2 Control Performance Criteria

4 Linear Process Representations

4.1 Discrete Linear State Space Process Representation

4.1.1 Discrete Linear State Space Model

4.1.2 Discrete Linear State Space Uncertainty Description

4.2 Discrete Linear Predictive Process Representation

4.2.1 Derivation of the Model Predictive Representation

4.2.2 Relation With Other Linear Process Representations

4.2.3 Special Cases

4.3 Model Predictive Representation for the Heavy Oil Fractionator

5 Linear Unconstrained Control

5.1 The Transfer Function Form (IMC)

5.1.1 The IMC Structure

5.1.2 Design Procedure

5.1.3 SISO Design

5.2 The Optimization Form

5.2.1 The Predictive Control Problem

5.2.2 Stability Theorems and Tuning Parameters

5.2.3 Nominal Design of Unconstrained Controllers for the Heavy Oil Fractionator

5.3 Comparison with Existing Techniques

5.3.1 Proportional Integral Derivative Controller

5.3.2 The Smith Predictor

5.3.3 Dahlin's Controller

5.3.4 Model Algorithmic Control

5.3.5 The Linear Quadratic Controller

5.4 Analysis of Linear Unconstrained Controllers

5.4.1 Nominal Performance

5.4.2 Robust Stability

5.4.3 Analysis of Unconstrained Controllers for the Heavy Oil Fractionator

6 Linear Model Predictive Control

6.1 The Dynamic Matrix Control Formulation

6.1.1 The DMC Constraint Equations

6.1.2 The Quadratic Programming Problem

6.1.3 Tuning of DMC

6.2 Implementation of DMC

6.2.1 Identification

6.2.2 Off-line Design

6.2.3 On-line Implementation

6.3 Comparison With Other MPC Algorithms

6.4 Nominal Design of Constrained Controllers for the Heavy Oil Fractionator

6.4.1 Tuning Parameters Used in DMC

6.4.2 Constrained DMC Algorithm

6.4.3 Comparison With Single Variable Controllers

7 Linear Fundamental Control Problem

7.1 A Process Control Algorithm Based On the Fundamental Control Problem

7.1.1 The Model Predictive Process Representation

7.1.2 The Computation of Future Moves

7.1.3 A Simple Example

7.2 Comparison With Other Robust Control Approaches

7.2.1 Infinity Norm Robust Model Predictive Control

7.2.2 The Structured Singular Value Theory

7.2.3 The Fundamental Control Problem and Robust Control Theory

7.3 Solution of the Fundamental Control Problem for the Heavy Oil Fractionator

7.3.1 Robust Stability of the Heavy Oil Fractionator Controllers

7.3.2 The Two-Level Optimization Approach Applied to the Heavy Oil Fractionator Control Problem

8 Design Methodologies and the Fundamental Control Problem

8.1 Standard Design Procedure

8.2 New Design Procedure

8.2.1 The Design Validation Problem

8.2.2 The Design Analysis Problem

8.3 Example of the Solution of the Design Analysis Problem

8.4 Summary and Future Directions

9 Computers in Manufacturing: The Role of Emerging Technologies

9.1 Efficiency and Effectiveness in the Application of Computers to Manufacturing

9.1.1 The Nature of Technological Change

9.1.2 Manufacturing Computer Systems

9.1.3 Efficiency in Manufacturing Computer Systems

9.1.4 Effectiveness in Manufacturing Computer Systems

9.1.5 Conclusions

9.2 Symbolic and Subsymbolic Processing: Process States, Dynamics, and Causality

9.2.1 Symbolic Processing

9.2.2 Subsymbolic Processing

9.2.3 Combining Symbolic and Subsymbolic Processing

9.2.4 Process Understanding Systems

9.2.5 Conclusions

9.3 Expert Systems and Neural Networks: An Overview

9.3.1 Expert Systems

9.3.2 Neural Networks

A Zero Offset For Ramp Inputs

B Mathematical Definitions

C Convexity of the Fundamental Control Problem Controller Quadratic Objective Function with Respect to Uncertain Gain Parameters



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About the Author

David M. Prett

Carlos E. García

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