Prett / Morari The Shell Process Control Workshop

1. Auflage 2013
ISBN: 978-1-4831-0223-8
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 386 Seiten, Web PDF

Shell Process Control Workshop covers the proceedings of a workshop of the same name, held in Houston, Texas on December 15, 1986. The said workshop seeks to improve the communication process between academic researchers, industrial researchers, and the engineering community in the field of process control, and in turn improve understanding of the nature of the control problems. The book covers topics such as design methodology based on the fundamental control; expert systems in process control and optimization; artificial intelligence; and adaptive control for processes. Also covered are topics such the approach of systems engineering to process modeling; modeling and control of dispersed phase systems; and advances in the use of the internal model control. The text is recommended for researchers and practitioners in the field of engineers who would like to know more about process control and modeling.

Autoren/Hrsg.

Prett, David M.

Morari, Manfred

Inhaltsverzeichnis

1;Front Cover;1
2;The Shell Process Control Workshop;2
3;Copyright Page;3
4;Table of Contents;4
5;ACKNOWLEDGMENT;6
6;OBJECTIVES;9
7;AUTHOR INDEX;12
8;SCHEDULE OF EVENTS;13
9;Chapter 1. Workshop Papers;18
9.1;Design Methodology Based On the Fundamental Control Problem Formulation;20
9.1.1;Abstract;20
9.1.2;1 Summary;20
9.1.3;2 Introduction;21
9.1.4;3 The Fundamental Control Problem;23
9.1.5;4 Survey of Existing Control Methodologies;26
9.1.6;5 A Design Procedure for Process Control;29
9.1.7;6 Areas of Research for the Realization of the Fundamental Control Problem;31
9.1.8;7 References;32
9.2;Control of Autoclave Processing of Polymeric Composites;44
9.2.1;Abstract;44
9.2.2;Introduction;44
9.2.3;Component Manufacturing;45
9.2.4;Motivation for Control;47
9.2.5;Process Control;49
9.2.6;The Role of Academia in Control Research;51
9.2.7;Summary;52
9.2.8;References;52
9.3;Expert Systems in Process Control and Optimization A Perspective;54
9.3.1;Abstract;54
9.3.2;Introduction;54
9.3.3;Artificial Intelligence and Process Control;55
9.3.4;Heuristics in Control Applications;56
9.3.5;Technology Transfer;57
9.3.6;Expert Apprentices;57
9.3.7;Symbolic Programming;59
9.3.8;The Knowledge Engineer;60
9.3.9;Machine Learning;60
9.3.10;Conclusions;61
9.3.11;References;63
9.4;An Artificial Intelligence Perspective in the Design of Control Systems for Complete Chemical Processes;66
9.4.1;Abstract;66
9.4.2;I Introduction;66
9.4.3;II A Model for the Plant Control System Design Procedure and Its Characteristics;70
9.4.4;II.A The State of the Control System Design;71
9.4.5;II.B The Goal Structure of the Design Process and Its Rationale;72
9.4.6;II.C Design Decisions and Their Rationale;75
9.4.7;II.D Controlling the Path of the Design Process;77
9.4.8;II.E "Learning" in Plant Control System Design;77
9.4.9;III Knowledge-Based Expert System Methodologies;78
9.4.10;III.A Knowledge Representation;79
9.4.11;III.B Inference Mechanisms and Explanation Facilities;81
9.4.12;III.C Strategies for Controlling the Design Procedure;82
9.4.13;IV Computing Environment and Programming Style: The "Control Design-Kit";83
9.4.14;IV.A Computing Environment;85
9.4.15;IV.B Programming Style;86
9.4.16;IV.C The "CONTROL DESIGN-KIT";86
9.4.17;V Summary;89
9.4.18;References;89
9.5;Process Identification - Past. Present. Future;96
9.5.1;Abstract;96
9.5.2;1 Summary;96
9.5.3;2 Introduction;96
9.5.4;3 Model Identification Overview;98
9.5.5;4 Process Data Collection;98
9.5.6;5 Process Representation;102
9.5.7;6 Identification Accuracy Criteria;104
9.5.8;7 Identification Approaches;106
9.5.9;8 Identification Example;113
9.5.10;9 Conclusions;114
9.5.11;10 References;116
9.6;Adaptive Control Software for Processes with Significant Deadtime;122
9.6.1;Abstract;122
9.6.2;I. Introduction;122
9.6.3;II. Adaptive Inferential (Internal Model) Control;123
9.6.4;III. Intune Software;125
9.6.5;IV. Application of Intune to a Laboratory Heat Exchanger;130
9.6.6;References;134
9.7;A Systems Engineering Approach to Process Modeling;156
9.7.1;Abstract;156
9.7.2;1 Introduction;157
9.7.3;2 Systems Engineering: Some General Thoughts;160
9.7.4;3 A Qualitative Assessment Of Cause And Effect Relationship;165
9.7.5;4 A More Quantitative Assessment, The Relative Gain Matrix;168
9.7.6;5 Further Improvements In Modeling, The Conservation Principle Models;169
9.7.7;6 Merging Empirical Models With Fundamental Principles, The Empirical Residence Time Distribution For Accumulation Dynamics.;172
9.7.8;7 The ARMA Model;174
9.7.9;8 Learning From The Basic Principles, First Order Processes;175
9.7.10;9 Learning From The Basic Principles, The Stoichiometric Law;190
9.7.11;10 Conclusion;196
9.7.12;References;197
9.8;Modelling and Control of Dispersed Phase Systems;200
9.8.1;Abstract;200
9.8.2;1 Introduction;200
9.8.3;2 Model Development;201
9.8.4;3 Crystallization;203
9.8.5;4 Emulsion Polymerization;209
9.8.6;5 Measurement Technology;221
9.8.7;6 Conclusions;221
9.8.8;Acknowledgements;223
9.8.9;References;223
9.9;Robust Control An Overview and Some New Directions;230
9.9.1;I Introduction;230
9.9.2;II Mathematical Background;230
9.9.3;III The (F,P,L,C) Configuration and its Stability Properties;232
9.9.4;IV Robustness for Linear Time Invariant Systems;235
9.9.5;V Robustness for Linear Time-Varying Systems;237
9.9.6;VI D iscussion- Conclusions;238
9.9.7;Acknowledgments;238
9.9.8;References;239
9.10;An Overview of Nonlinear Geometrical Methods for Process Control *;242
9.10.1;Abstract;242
9.10.2;1 Introduction;242
9.10.3;2 Feedback Linearization;244
9.10.4;3 Linearization by Inversion;249
9.10.5;4 Exact Local Linearization;252
9.10.6;5 Partial Linearization;257
9.10.7;6 Applications;258
9.10.8;7 Acknowledgements;264
9.10.9;8 Notation;264
9.10.10;References;265
9.11;Recent Advances in the Use of the Internal Model Control Structure for the Synthesis of Robust Multivariable Controllers*;268
9.11.1;Abstract;268
9.11.2;1 Preliminaries;268
9.11.3;2 Step 1: Design of Q;270
9.11.4;3 Model Uncertainty;275
9.11.5;4 Step 2: Design of F;279
9.11.6;Appendix A;286
9.11.7;Appendix B;289
9.11.8;C References;291
9.11.9;D Acknowledgements;291
9.12;Characterization of Distillation Nonlinearity for Control System Design and Analysis;296
9.12.1;Abstract;296
9.12.2;I Introduction;296
9.12.3;II Characterization of Distillation Nonlinearity;298
9.12.4;III Compensating for Process Nonlinearity;301
9.12.5;IV Summary;302
9.12.6;References;302
9.13;Selecting Sensor Location and Type for Multivariable Processes;308
9.13.1;Abstract;308
9.13.2;Introduction;308
9.13.3;Ethanol-Water Example;308
9.13.4;Singular Value Decomposition;309
9.13.5;Determining Sensor Locations;310
9.13.6;Summary;314
9.13.7;References;315
9.14;Three Critiques of Process Control Revisited a Decade Later;326
9.14.1;Abstract;326
9.14.2;Introduction;326
9.14.3;Modern Linear (Multivariable) Control Theory;327
9.14.4;Modal/Pole Placement Control;328
9.14.5;Decoupling;328
9.14.6;Multivariable Frequency Domain Design Techniques;328
9.14.7;Linear Quadratic Optimal Control;328
9.14.8;Model Requirements/Inadequacies;329
9.14.9;Open Problems;331
9.14.10;Effect of Process Design on Process Control;332
9.14.11;Choice of Control Structure;332
9.14.12;Open Problems;333
9.14.13;Process Constraints;333
9.14.14;Operator Acceptance;334
9.14.15;Use and Misuse of "Optimal Control";334
9.14.16;Nonlinear/Adaptive Systems;335
9.14.17;Conclusions;335
9.14.18;Acknowledgements;336
9.14.19;References;336
10;Chapter 2. Discussion Sessions;340
10.1;Introduction;342
10.2;2.1 "Design Methodology Based on the Fundamental Control Problem Formulation," C. E. Garcia (Speaker) and D. M. Prett;342
10.3;2.2 "Control of Autoclave Processing of Polymeric Composites," B. R. Holt (Speaker);344
10.4;2.3 "Expert Systems in Process Control and Optimization: A Perspective," D. B. Garrison (Speaker), D. M. Prett, and P. E. Steacy;347
10.5;2.4 "An Artificial Intelligence Perspective in the Design of Control Systems for Complete Chemical Processes," G. Stephanopoulos, J. Johnston (Speaker), and R. Lakshmanan (Speaker);349
10.6;2.5 "Process Identification - Past, Present, Future," D. M. Prett, T. A. Skrovanek, and J. F. Pollard (Speaker);350
10.7;2.6 "Adaptive Control Software for Processes with Significant Deadtime," C. Brosilow (Speaker), W. Belias, and C. Cheng;351
10.8;2.7 "A Systems Engineering Approach to Process Modeling," O. A. Asbjørnsen (Speaker);353
10.9;2.8 "Modeling and Control of Dispersed Phase Systems," J. B. Rawlings (Speaker);354
10.10;2.9 "Robust Control, An Overview and Some New Directions," V. Manousiouthakis (Speaker);356
10.11;2.10 "An Overview of Nonlinear Geometrical Methods for Process Control," J. C. Kantor (Speaker);357
10.12;2.11 "Recent Advances in the use of the Internal Model Control Structure for the Synthesis of Robust Multivariable Controllers," E. Zafiriou (Speaker);358
10.13;2.12 "Characterization of Distillation Nonlinearity for Control System Design and Analysis," K. McDonald (Speaker);359
10.14;2.13 "Selecting Sensor Location and Type for Multivariable Processes," C. Moore (Speaker), J. Hackney, and D. Canter;360
10.15;2.14 "Three Critiques of Process Control Revisited a Decade Later," M. Morari (Speaker);361
11;Chapter 3. Shell Control Problem;366
11.1;3.1 Introduction;368
11.2;3.2 Tutorial Sessions Summary;368
11.3;3.3 Problem Description;372
11.4;3.4 Schedule of Events;378
12;Chapter 4. Summary;380
12.1;Preamble;382
12.2;Summary Discussion;382