McAvoy / Arkun / Zafiriou Model Based Process Control

Proceedings of the IFAC Workshop, Atlanta, Georgia, USA, 13-14 June, 1988
1. Auflage 2014
ISBN: 978-1-4832-9823-8
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band Volume 82, 172 Seiten, Web PDF

Reihe: IFAC Workshop Series

Presented at this workshop were mathematical models upon which process control is based and the practical applications of this method of control within industry; case studies include examples from the paper and pulp industry, materials industry and the chemical industry, among others. From these presentations emerged a need for further research and development into process control. Containing 19 papers these Proceedings will be a valuable reference work for all those involved in the designing of continuous production processes for industry and for the end user involved in the practical application of process control within their manufacturing process.

Autoren/Hrsg.

McAvoy, T. J.

Arkun, Y.

Zafiriou, E.

Inhaltsverzeichnis

1;Front Cover;1
2;Model Based Process Control;4
3;Copyright Page;5
4;Table of Contents;10
5;Foreword;8
6;PART 1: TUTORIAL;12
6.1;CHAPTER 1. MODEL PREDICTIVE CONTROL: THEORY
AND PRACTICE;12
6.1.1;ABSTRACT;12
6.1.2;INTRODUCTION;12
6.1.3;HISTORICAL BACKGROUND;13
6.1.4;MODELS;14
6.1.5;MPC ALGORITHM FORMULATIONS;14
6.1.6;ANALYSIS;15
6.1.7;UNCONSTRAINED MPC;15
6.1.8;CONSTRAINED MPC;19
6.1.9;ROBUSTNESS;20
6.1.10;CONCLUSIONS;21
6.1.11;ACKNOWLEDGEMENT;21
6.1.12;REFERENCES;21
7;PART 2: INVITED INDUSTRIAL CASE STUDIES;24
7.1;CHAPTER 2. CASE STUDIES OF MODEL-PREDICTIVE
CONTROL IN PULP AND PAPER
PRODUCTION;24
7.1.1;ABSTRACT;24
7.1.2;INTRODUCTION;24
7.1.3;THE EVAPORATION PROCESS;24
7.1.4;CONTROL OF THE FULL-SCALE EVAPORATOR;28
7.1.5;SIMULATED CONTROL OF EVAPORATOR WITH STORAGE TANKS;29
7.1.6;SUMMARY;29
7.1.7;ACKNOWLEGEMENTS;30
7.1.8;LITERATURE CITED;30
7.2;CHAPTER 3. DESIGN CONSIDERATIONS FOR A
HYDROCRACKER PREFLASH COLUMN
MULTIVARIABLE CONSTRAINT
CONTROLLER;34
7.2.1;INTRODUCTION;34
7.2.2;PROCESS DESCRIPTION;34
7.2.3;DESIGN CONSIDERATIONS;35
7.2.4;PROCESS IDENTIFICATION;37
7.2.5;SUMMARY;38
7.3;CHAPTER 4. THE IDOCOM–M CONTROLLER;42
7.3.1;INTRODUCTION;42
7.3.2;REQUIREMENTS FOR INDUSTRIAL MULTIVARIABLE CONTROLLERS;42
7.3.3;THE IDCOM–M CONTROLLER;43
7.3.4;EXAMPLES;45
7.3.5;CONCLUSION;45
7.3.6;REFERENCES;47
7.4;CHAPTER 5. SMOC, A BRIDGE BETWEEN STATE SPACE
AND MODEL PREDICTIVE CONTROLLERS:
APPLICATION TO THE AUTOMATION OF A
HYDROTREATING UNIT;48
7.4.1;REFERENCES;54
7.5;CHAPTER 6. STATE SPACE MODEL PREDICTIVE
CONTROL OF A MULTISTAGE
ELECTROMETALURGICAL PROCESS;58
7.5.1;INTRODUCTION;58
7.5.2;PROPERTIES OF THE PRESENT METHOD;59
7.5.3;THE APPLICATION OF MODEL PREDICTIVE CONTROL TO A MULTISTAGE ELECTROMETALURGICAL PROCESS;59
7.5.4;THE MODEL;59
7.5.5;THE OBJECTIVE FUNCTIONAL;60
7.5.6;SOLUTION STRATEGY;60
7.5.7;SIMULATION EXPERIMENTS;61
7.5.8;CONCLUSION;62
7.5.9;'ACKNOWLEDGEMENT;62
7.5.10;NOMENCLATURE;62
7.5.11;REFERENCES;62
7.6;CHAPTER 7. MODEL-BASED DUAL COMPOSITION
CONTROL OF AN INDUSTRIAL PROPYLENE
SPLITTER;66
7.6.1;INTRODUCTION;66
7.6.2;PROCESS DESCRIPTION;66
7.6.3;MODEL BASED CONTROL;67
7.6.4;REFERENCES;70
8;PART 3: CONTRIBUTED PAPERS;74
8.1;CHAPTER 8. DISTURBANCE FEEDBACK IN MODEL
PREDICTIVE CONTROL SYSTEMS;74
8.1.1;ABSTRACT;74
8.1.2;INTRODUCTION;74
8.1.3;STATE SPACE FORM OF THE PROCESS MODEL;75
8.1.4;PREDICTION AND FEEDBACK OF RESIDUAL CORRECTION TERM;76
8.1.5;EXPERIMENTAL RESULTS;77
8.1.6;CONCLUSIONS;78
8.1.7;LITERATURE CITED;78
8.1.8;APPENDIX A;79
8.2;CHAPTER 9. DEVELOPMENT OF A MULTIVARIABLE
FORWARD MODELING CONTROLLER;80
8.2.1;I. INTRODUCTION;80
8.2.2;II. ALGORITHM DEVELOPMENT;81
8.2.3;III. FMC PERFORMANCE;83
8.2.4;IV. SUMMARY;84
8.2.5;APPENDIX;84
8.2.6;REFERENCES;84
8.3;CHAPTER 10. A STUDY ON ROBUST STABILITY OF MODEL
PREDICTIVE CONTROL;86
8.3.1;ABSTRACT;86
8.3.2;INTRODUCTION;86
8.3.3;GENERAL DESCRIPTION OF THE MODEL PREDICTIVE CONTROL;86
8.3.4;ROBUST STABILITY OF SISO SYSTEMS;87
8.3.5;ROBUST STABILITY AND COINCIDENCE HORIZON;88
8.3.6;ROBUST STABILITY OF MULTIVARIABLE SYSTEMS;89
8.3.7;CONCLUSION;89
8.3.8;APPENDIX;89
8.3.9;REFERENCE;91
8.4;CHAPTER 11. PREDICTIVE CONTROL: A REVIEW AND
SOME NEW STABILITY RESULTS;92
8.4.1;1.Introduction;92
8.4.2;2. Underlying Models;93
8.4.3;3. Cost, Control Action, and Command Signal;93
8.4.4;4. Controller Structure;94
8.4.5;5. Stability Properties;95
8.4.6;6. Conclusions;96
8.4.7;REFERENCES;97
8.5;CHAPTER 12. ROBUSTNESS AND TUNING OF ON-LINE
OPTIMIZING CONTROL ALGORITHMS;100
8.5.1;Abstract;100
8.5.2;1 Introduction;100
8.5.3;2 The On-Line Optimization Problem;100
8.5.4;3 Formulation of the Problem as Contraction Mapping;101
8.5.5;4 Stability Conditions;101
8.5.6;5 Illustration;103
8.5.7;6 Conclusions;104
8.5.8;Acknowledgements;104
8.5.9;References;104
8.6;CHAPTER 13. APPLICATION OF SINGULAR VALUE
METHODS FOR IDENTIFICATION AND
MODEL BASED CONTROL OF DISTRIBUTED
PARAMETER SYSTEMS;106
8.6.1;INTRODUCTION;106
8.6.2;DPS SINGULAR VALUE THEORY;107
8.6.3;MODEL BASED CONTROL;109
8.6.4;EXAMPLES;111
8.6.5;SUMMARY;112
8.6.6;REFERENCES;112
8.7;CHAPTER 14. MODEL-BASED CONTROL FOR SYSTEMS IN
OPERATOR DESCRIPTION;114
8.7.1;INTRODUCTION;114
8.7.2;SYSTEM DESCRIPTION;114
8.7.3;CONVENTIONAL MODEL-BASED SCHEMES;115
8.7.4;ALTERNATIVE APPLICATIONS;115
8.7.5;SENSITIVITY ASPECTS;117
8.7.6;CONCLUDING REMARKS;118
8.7.7;ACKNOWLEDGEMENT;118
8.7.8;REFERENCES;118
8.8;CHAPTER 15. GENERIC MODEL CONTROL — THEORY AND
APPLICATIONS;122
8.8.1;ABSTRACT;122
8.8.2;1.0 INTRODUCTION;122
8.8.3;2.0 CONTROL STRUCTURE;123
8.8.4;3.0 RESPONSE SPECIFICATION;124
8.8.5;4.0 LINEAR CONTROL IN A GMC FRAMEWORK;124
8.8.6;5.0 MODEL STRUCTURE AND DIMENSIONALITY;125
8.8.7;6.0 MULTIVARIABLE DEADTIME SYSTEMS;127
8.8.8;7.0 SUMMARY;128
8.8.9;8.0 ACKNOWLEDGEMENTS;128
8.8.10;9.0 REFERENCES;128
8.9;CHAPTER 16. INTEGRATED MODEL BASED CONTROL OF
MULTIVARIABLE NONLINEAR SYSTEMS;132
8.9.1;INTRODUCTION;132
8.9.2;THEORY;132
8.9.3;APPLICATION TO DISTILLATION COLUMN CONTROL;134
8.9.4;RESULT OF THE EXAMPLE STUDY;135
8.9.5;CONCLUSIONS;136
8.9.6;NOTATIONS;137
8.9.7;REFERENCES;137
8.10;CHAPTER 17. MODEL-PREDICTIVE CONTROL AND
SENSITIVITY ANALYSIS FOR CONSTRAINED
NONLINEAR PROCESSES;140
8.10.1;Abstract;140
8.10.2;Keywords;140
8.10.3;Introduction;140
8.10.4;Solution Methods;141
8.10.5;Parametric Sensitivity;141
8.10.6;Second Order Sensitivity;142
8.10.7;Computational results;142
8.10.8;Example 1;142
8.10.9;Example 2;144
8.10.10;Conclusion;145
8.10.11;References;145
8.11;CHAPTER 18. CONCENTRATION PROFILE ESTIMATION
AND CONTROL IN BINARY DISTILLATION;148
8.11.1;Abstract;148
8.11.2;Introduction;148
8.11.3;The Control Problem;149
8.11.4;Model Reduction;149
8.11.5;System Analysis;150
8.11.6;Comparison of nonlinear and linearized reduced model;150
8.11.7;Modal Analysis of the Linear Model;150
8.11.8;Measures of Observability, Controllability and Disturbability;151
8.11.9;Measurement Location;151
8.11.10;Interaction Measures;151
8.11.11;System Analysis Summary;152
8.11.12;Control System Synthesis;152
8.11.13;State Estimation and Proportional Feedback;152
8.11.14;Proportional-integral Feedback;152
8.11.15;Concentration Profile Estimation;153
8.11.16;Conclusions;154
8.11.17;References;154
8.12;CHAPTER 19. AN APPROACH TO MULTIVARIABLE
PROCESS IDENTIFICATION;156
8.12.1;ABSTRACT;156
8.12.2;INTRODUCTION;156
8.12.3;2. A MULTIVARIABLE IDENTIFICATION METHOD;156
8.12.4;3. RESULTS AND DISCUSSION;160
8.12.5;5.CONCLUSIONS;161
8.12.6;REFERENCES;161
9;AUTHOR INDEX;164