Rawlings Dynamics and Control of Chemical Reactors, Distillation Columns and Batch Processes (DYCORD'95)

1. Auflage 2014
ISBN: 978-1-4832-9688-3
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 502 Seiten, Web PDF

Reihe: IFAC Postprint Volume

Three important areas of process dynamics and control: chemical reactors, distillation columns and batch processes are the main topics of discussion and evaluation at the IFAC Symposium on Dynamics and Control of Chemical Reactors, Distillation Columns and Batch Processes (DYCORD '95). This valuable publication was produced from the latest in the series, providing a detailed assessment of developments of key technologies within the field of process dynamics and control.

Autoren/Hrsg.

Rawlings, J. B.

Inhaltsverzeichnis

1;Front Cover;1
2;Dynamics and Control of Chemical Reactors, Distillation Columns and Batch Processes (Dycord+ '95);2
3;Copyright Page;3
4;Acknowledgements;5
5;TABLE OF CONTENTS;6
6;PART I: PLENARY PAPER I;12
6.1;CHAPTER 1. A CONTEMPORARY INDUSTRIAL PERSPECTIVE ON PROCESS CONTROL THEORY AND PRACTICE;12
6.1.1;1 INTRODUCTION;12
6.1.2;2 RE-EXAMINING "PROCESS CONTROL";13
6.1.3;3 A BRIEF HISTORICAL PERSPECTIVE;14
6.1.4;4 CONTEMPORARY ISSUES;15
6.1.5;5 ANTICIPATING THE FUTURE;18
6.1.6;6 SUMMARY/CONCLUSION;19
6.1.7;REFERENCES;19
7;Part II: CHEMICAL REACTORS I;20
7.1;CHAPTER 2. CONTROL SYSTEM IMPROVEMENT OF AN INDUSTRIAL CHEMICAL REACTOR;20
7.1.1;1. INTRODUCTION;20
7.1.2;2. OUTLINE OF EXISTING PLANT;20
7.1.3;3. MODELING OF EXISTING PLANT;21
7.1.4;4. BASIC STRATEGY FOR IMPROVEMENT;22
7.1.5;5. ADVANCED STRATEGY FOR IMPROVEMENT;23
7.1.6;6. CONCLUSION AND FUTURE DEVELOPMENT;25
7.1.7;7. REFERENCES;25
7.2;CHAPTER 3. COMPUTATIONAL FLUID DYNAMICS AS A TOOL FOR CHEMICAL REACTOR OPTIMIZATION;26
7.2.1;1. INTRODUCTION;26
7.2.2;2. REACTOR MODEL;26
7.2.3;3. EXAMPLES OF FLUID FLOW SIMULATION;27
7.2.4;4. CONCLUSIONS;30
7.2.5;REFERENCES;30
7.3;CHAPTER 4. Control of Forced Cyclic Process;32
7.3.1;1. INTRODUCTION;32
7.3.2;2. METHODS;33
7.3.3;3. STATIC BEHAVIOUR;34
7.3.4;4. DYNAMIC BEHAVIOUR;36
7.3.5;5. CONTROL PROBLEM;37
7.3.6;6. CONCLUSIONS;37
7.3.7;7. LITTERATURE;37
7.4;CHAPTER 5. FUZZY LOGIC CONTROLLER DESIGN FOR PH-CONTROL IN A CSTR;38
7.4.1;1. INTRODUCTION;38
7.4.2;2. DESCRIPTION AND MODELLING OF THE PLANT;39
7.4.3;3. FUZZY CONTROLLER DESIGN BASED ON HEURISTICS ALONE;39
7.4.4;4. APPROXIMATION OF OPTIMAL CONTROLLERS BY A FUZZY SYSTEM;40
7.4.5;5. MODEL BASED FUZZY CONTROLLER DESIGN;41
7.4.6;6. CONCLUSIONS;43
7.4.7;REFERENCES;43
7.5;CHAPTER 6. RELIABLE AND EFFICIENT OPTIMIZATION STRATEGIES FOR NONLINEAR MODEL PREDICTIVE CONTROL;44
7.5.1;1. INTRODUCTION;44
7.5.2;2. A MULTIPLE SHOOTING FORMULATION FOR PROCESS CONTROL;45
7.5.3;3. EXAMPLES;47
7.5.4;4. CONCLUSIONS;49
7.5.5;ACKNOWLEDGMENTS;49
7.5.6;5. REFERENCES;49
8;PArt III:CHEMICAL REACTORS II;50
8.1;CHAPTER 7. OPTIMAL ESTIMATION OF STATES IN DIFFERENTIAL-ALGEBRAIC EQUATION SYSTEMS;50
8.1.1;1. INTRODUCTION;50
8.1.2;2. OPTIMAL ESTIMATION FOR DAE SYSTEMS;50
8.1.3;3. APPLICATION TO A FIXEDBED REACTOR;51
8.1.4;4. PERFORMANCE OF THE REACTOR ESTIMATOR;53
8.1.5;5. CONCLUSIONS;55
8.1.6;REFERENCES;55
8.2;CHAPTER 8. USE OF ITERATIVE DYNAMIC PROGRAMMINGIN OPTIMIZATION OF REACTOR SYSTEMS;56
8.2.1;1. INTRODUCTION;56
8.2.2;2. OPTIMAL CONTROL PROBLEM;56
8.2.3;3. IDP ALGORITHM;57
8.2.4;4. NUMERICAL RESULTS;57
8.2.5;5. CONCLUSIONS;60
8.2.6;REFERENCES;60
8.3;CHAPTER 9. HARD CONSTRAINTS IN CONTROL AND STATE VARIABLES OF MULTIVARIABLE NONLINEAR PROCESSES RESOLVED BY ELEMENTARY NONLINEAR DECOUPLING;62
8.3.1;1. INTRODUCTION;62
8.3.2;2. SHORT REVIEW OF THE END ALGORITHM;62
8.3.3;3. THE END ALGORITHM WITH CONSTRAINED STATE VARIABLES;64
8.3.4;4. END CONTROL OF A STIRRED TANK REACTOR WITH TWO CONSECUTIVE REACTIONS;64
8.3.5;5. CONCLUSION;65
8.3.6;6. ACKNOWLEDGEMENTS;65
8.3.7;7. REFERENCES;65
8.4;CHAPTER 10. TIME-VARIABLE MODELS FOR MIXING PROCESSES UNDER UNSTEADY FLOW AND VOLUME;68
8.4.1;1. INTRODUCTION;68
8.4.2;2. TIME-VARYING AGE DISTRIBUTIONS;69
8.4.3;3. MODELS AND THEIR INTERCONNECTIONS;69
8.4.4;4. PRACTICAL TESTS;72
8.4.5;5. CONCLUSION;73
8.4.6;6. REFERENCES;73
8.5;CHAPTER 11. GENERAL METHODS OF KINETIC MODEL REDUCTION;74
8.5.1;1. INTRODUCTION;74
8.5.2;2. REACTOR MODELING;75
8.5.3;3. VS FORMULATION FOR NETWORK REDUCTION;75
8.5.4;4. GA FORMULATION FOR NETWORK REDUCTION;77
8.5.5;5. TEST PROBLEM;77
8.5.6;6. RESULTS;78
8.5.7;7. CONCLUSION;79
8.5.8;8. REFERENCES;79
8.6;CHAPTER 12. ROBUST DECENTRALIZED CONTROL OF A CSTR WITH COMPLEX REACTION SCHEME;80
8.6.1;1. INTRODUCTION;80
8.6.2;2. CONTROLLER DESIGN BY FREQUENCY RESPONSE APPROXIMATION;81
8.6.3;3. THE SET OF ALL STABILIZING DECENTRALIZED CONTROLLERS;81
8.6.4;4. APPLICATION TO A CSTR;82
8.6.5;5. CONCLUSIONS;85
8.6.6;ACKNOWLEDGEMENTS;85
8.6.7;REFERENCES;85
9;Part IV: DISTILLATION COLUMNS I;86
10;CHAPTER 13. INPUT MULTIPLICITY AND RIGHT HALF PLANE ZEROS IN IDEAL TWO-PRODUCT DISTILLATION;86
10.1;1. INTRODUCTION;86
10.2;2. INTRODUCTORY EXAMPLE;86
10.3;3. DV-CONFIGURATION;87
10.4;4. OTHER CONFIGURATIONS;88
10.5;5. EFFECT OF OPERATING CONDITIONS;89
10.6;6. DYNAMICS;89
10.7;7. INPUT MULTIPLICITY WITH MASS INPUTS;90
10.8;8. SPECIFICATION OF TWO OUTPUTS;90
10.9;9. CONCLUSIONS;91
10.10;REFERENCES;91
11;CHAPTER 14. HETEROGENEOUS AZEOTROPIC DISTILLATION INVOLVING AN EMBEDDED TWO-LIQUID PHASE REGION;92
11.1;1. INTRODUCTION;92
11.2;2. PHASE EQUILIBRIA AND RESIDUE CURVES;93
11.3;3. DISTILLATION TOWER;93
11.4;4. STEADY-STATE SIMULATION;93
11.5;5. PROCESS DYNAMICS;94
11.6;6. CONCLUSION;95
11.7;7. ACKNOWLEDGMENTS;95
11.8;REFERENCES;95
12;CHAPTER 15. HIERARCHICAL SUB-OPTIMAL CONTROL OF BATCH DISTILLATION WITH SLOP RECYCLING;98
12.1;INTRODUCTION;98
12.2;LITERATURE OVERVIEW;99
12.3;SINGLE-RUN POLICIES;100
12.4;SLOP RECYCLE POLICIES;101
12.5;COORDINATOR HIERARCHY;102
12.6;SCHEDULER RELATIONS;102
12.7;CONCLUSIONS;103
12.8;SYMBOLS;103
12.9;REFERENCES;103
13;CHAPTER 16. HIGH PERFORMANCE DISTILLATION COLUMN CONTROL THROUGH NOVEL CONTROL CONFIGURATIONS;104
13.1;1 INTRODUCTION;104
13.2;2 MODEL TRANSFORMATION;104
13.3;3 AN EXAMPLE COLUMN;106
13.4;4 DESIGN NEW CONTROL CONFIGURATIONS;106
13.5;5 CONCLUSIONS;109
13.6;6 REFERENCES;109
14;CHAPTER 17. A DAE FRAMEWORK FOR MODELING AND CONTROL OF REACTIVE DISTILLATION COLUMNS;110
14.1;1. INTRODUCTION;110
14.2;2. DYNAMIC MODELING AND SIMULATION;110
14.3;3. CONTROL PROBLEM;112
14.4;4. CONCLUSIONS;114
14.5;5. ACKNOWLEDGMENT;114
14.6;6. REFERENCES;114
15;CHAPTER 18. IDENTIFICATION OF A PILOT PLANT REACTIVE DISTILLATION PROCESS USING RBF NETWORKS;116
15.1;1. INTRODUCTION;116
15.2;2. PROCESS;117
15.3;3. EXPERIMENTS;117
15.4;4. NONLINEAR IDENTIFICATION;118
15.5;5. MODEL VALIDATION;119
15.6;6. RESULTS;119
15.7;7. CONCLUSIONS;121
15.8;8. REFERENCES;121
16;CHAPTER 19. REDUCED MODELING OF COMPLEX FLUID MLXTURES BY THE WAVELET-GALERKIN METHOD;122
16.1;1. INTRODUCTION;122
16.2;2. MODEL REDUCTION FOR COMPLEX FLUID MIXTURES;122
16.3;3. SOLUTION TECHNIQUES;123
16.4;4. WAVELET-GALERKIN METHOD;124
16.5;5. APPLICATION OF WAVELET-GALERKIN METHOD;125
16.6;6. CONCLUSIONS;127
16.7;7. REFERENCES;127
17;CHAPTER 20. AN OBJECT-ORIENTED METHOD FOR PROCESS MODELLING;128
17.1;1. INTRODUCTION;128
17.2;2. SYSTEM TOPOLOGY AND BEHAVIOUR;128
17.3;3. THE OBJECT-ORIENTED MODEL;129
17.4;4. MODELLING A CSTR;130
17.5;5. HC-FERROMANGANESE FURNACE;132
17.6;6. DISCUSSION;133
17.7;7. CONCLUSION;133
17.8;8. REFERENCES;133
18;CHAPTER 21. HYBRID SIMULATION OF FLEXIBLE BATCH PLANTS;134
18.1;INTRODUCTION;134
18.2;RECIPE BASED OPERATION;135
18.3;STRUCTURE OF THE SIMULATION PROGRAM;136
18.4;SIMULATION OF THE HYBRID SYSTEM;137
18.5;DETECTION OF EVENTS;138
18.6;CONCLUSION;139
18.7;ACKNOWLEDGEMENTS;139
18.8;REFERENCES;139
19;CHAPTER 22. NEURAL NETWORK BASED ESTIMATORS FOR A BATCH POLYMERIZATION REACTOR;140
19.1;1 INTRODUCTION;140
19.2;2 A BATCH POLYMERIZATION REACTOR;141
19.3;3 NEURAL NETWORKS WITH MIXED TYPES OF NEURONS;141
19.4;4 NEURAL NETWORK BASED INFERENTIAL ESTIMATORS;142
19.5;5 CONCLUSIONS;143
19.6;6 REFERENCES;144
20;CHAPTER 23. ALAMBIC - A SOFTWARE PACKAGE FOR OPTIMISING DESIGN AND OPERATION OF BATCH DISTILLATION COLUMNS;146
20.1;1. INTRODUCTION;146
20.2;2. ALAMBIC - OVERVIEW;147
20.3;3. CASE STUDIES;150
20.4;4. CONCLUSIONS;151
20.5;ACKNOWLEDGMENTS;151
20.6;REFERENCES;151
21;CHAPTER 24. COMPARISON OF INVERTED AND REGULAR BATCH DISTILLATION;152
21.1;1. INTRODUCTION;152
21.2;2. OPTIMAL OPERATION;153
21.3;3. THE PERFORMANCE OF "INVERTED" SEPARATIONS;155
21.4;4. IDEAL INVERTED COLUMN;156
21.5;5. CONCLUSION;156
21.6;ACKNOWLEDGEMENT;157
21.7;NOTATION;157
21.8;REFERENCES;157
21.9;APPENDIX;157
22;CHAPTER 25. EXPERIMENTAL EVALUATION OF A FAULT DETECTION AND IDENTIFICATION SCHEME FOR CHEMICAL PROCESSES;158
22.1;1. INTRODUCTION;158
22.2;2. PROCESS MODELLING AND CONTROL;159
22.3;3. SENSOR FAULT DETECTION;159
22.4;4. FAULT TOLERANT CONTROL STRATEGIES;160
22.5;5. EXPERIMENTAL RESULTS;160
22.6;6. CONCLUSIONS;163
22.7;7. NOTATION;163
22.8;ACKNOWLEDGEMENTS;163
22.9;8. REFERENCES;163
23;CHAPTER 26. STEADY STATE AND DYNAMIC SIMULATION OF FCC REACTOR UNITS;164
23.1;1. INTRODUCTION;164
23.2;2. RESULTS AND DISCUSSION;166
23.3;3. CONCLUSIONS;167
23.4;4. ACKNOWLEDGMENTS;167
23.5;REFERENCES;167
24;CHAPTER 27. DYNAMICS OF THE JAROSITE CONVERSION PROCESS;170
24.1;1. INTRODUCTION TO THE JAROSITE CONVERSION PROCESS;170
24.2;2. CONTROL OBJECTIVES AND PROCESS MODELLING;171
24.3;3. EXPERIMENTAL METHODS;171
24.4;4. PARAMETERS INVESTIGATED;171
24.5;5. DETERMINATION OF THE LEACHING REACTION RATE CONSTANT;172
24.6;6. DETERMINISTIC DYNAMIC MODEL;172
24.7;7. SENSITIVITY ANALYSIS;173
24.8;8. CONCLUSIONS;175
24.9;ACKNOWLEDGEMENTS;175
24.10;REFERENCES;175
24.11;NOMENCLATURE;175
25;CHAPTER 28. MODEL-BASED TEMPERATURE CONTROL OF FED-BATCH REACTORS;176
25.1;1. INTRODUCTION;176
25.2;2. TENDENCY MODEL OF THE PROCESS;177
25.3;3. MODEL-BASED CONTROL ALGORITHM;179
25.4;4. SIMULATION AND PHYSICAL STUDY OF THE ALGORITHM;180
25.5;5. CONCLUSIONS;181
25.6;ACKNOWLEDGEMENTS;181
25.7;REFERENCES;181
26;CHAPTER 29. PRACTICAL CONTROL METHODS FOR DISTILLATION COLUMNS USING NEURAL NETWORKS;182
26.1;1-INTRODUCTION;182
26.2;2-DISTILLAT10N COLUMN MODEL STUDIED.;183
26.3;3-NEURAL NETWORK ARCHITECTURE;183
26.4;4- INTERNAL MODEL CONTROL STRATEGY.;184
26.5;5- FEEDFORWARD COMPENSATION USING NN INVERSE PLANT MODEL;186
26.6;6- CONCLUSIONS;186
26.7;REFERENCES;187
26.8;ACKNOWLEDGMENTS;187
27;CHAPTER 30. FINE TUNING OF MULTILOOP PI CONTROLLERS USING FUZZY SET THEORY;188
27.1;1. INTRODUCTION;188
27.2;2. CONVENTIONAL MULTILOOP PI CONTROLLERS TUNING METHOD;189
27.3;3. FUZZY SET THEORY;189
27.4;4. PROPOSED TUNING METHOD USING FUZZY SET THEORY;189
27.5;5. EXAMPLE;192
27.6;ACKNOWLEDGMENT;193
27.7;REFERENCES;193
28;CHAPTER 31. MULTIVARIABLE CONTROL OF DISTILLATION COLUMN;196
28.1;1. INTRODUCTION;196
28.2;2. MULTIVARIABLE POLE ASSIGNMENT METHOD;196
28.3;3. DECOUPLING METHOD WITH PRECOMPENSATOR;197
28.4;4. DECOUPLING METHOD WITH PRECOMPENSATOR AND UNIT FEEDBACK;198
28.5;5. SIMULATION EXPERIMENTS;198
28.6;6. CONCLUSIONS;200
28.7;REFERENCES;200
29;CHAPTER 32. SIMULATION OF MULTICOMPONENT BATCH DISTILLATION WITH CHEMICAL REACTIONS PROCESSES;202
29.1;MNTRODUCTION;202
29.2;2-DYNAMIC MODEL DESCRIPTION;203
29.3;3 -SOLUTION OF THE MODEL EQUATIONS;204
29.4;4-RESULTS AND DISCUSSION;205
29.5;5-CONCLUSIONS;207
29.6;6-REFERENCES;207
30;CHAPTER 33. PHYSICAL IMPLICATIONS OF PERIODIC SOLUTIONS IN A FIXED BED REACTOR WITH RECYCLE;208
30.1;1. INTRODUCTION;208
30.2;2. METHOD;209
30.3;3. RESULTS;210
30.4;4. CONTROL STRUCTURE CONSIDERATIONS;211
30.5;5. CONCLUSION;213
30.6;SYMBOLS;213
30.7;REFERENCES;213
31;CHAPTER 34. Analysis of Process Dynamics Using Steady State Flowsheeting Tools;214
31.1;1. INTRODUCTION;214
31.2;2. DERIVATION OF AN APPROXIMATE DYNAMIC PLANT MODEL;214
31.3;3. A PLANT-WIDE CASE STUDY;216
31.4;4. CONCLUSIONS;219
31.5;5. REFERENCES;219
32;CHAPTER 35. NEURAL NETWORK IDENTIFICATION OF AN IN-LINE pH PROCESS;220
32.1;1. INTRODUCTION;220
32.2;2. PROCESS DESCRIPTION;221
32.3;3. RADIAL BASIS FUNCTION ANN MODELS;222
32.4;4. DEADTIME COMPENSATION;222
32.5;5. RESULTS;223
32.6;6. CONCLUSIONS;224
32.7;ACKNOWLEDGEMENTS;225
32.8;REFERENCES;225
33;CHAPTER 36. SOME ASPECTS OF INTEGRATED PROCESS OPERATION;226
33.1;1. INTRODUCTION;226
33.2;2. INTEGRATION ON PROCESSING UNIT LEVEL;227
33.3;3. INTEGRATION OF PROCESS OPERATION ON THE FLOWSHEET LEVEL;232
33.4;4. CONCLUDING REMARKS;237
33.5;5. ACKNOWLEDGEMENT;238
33.6;6. REFERENCES;238
34;CHAPTER 37. OPTIMIZATION IN MODEL BASED CONTROL1;240
34.1;1. INTRODUCTION;240
34.2;2. MODEL PREDICTIVE CONTROL;240
34.3;3. MODEL PREDICTIVE CONTROL OF NONLINEAR SYSTEMS;243
34.4;4. ROBUST MPC;246
34.5;5. OUTPUT FEEDBACK MPC;249
34.6;6. ADAPTIVE MPC;250
34.7;7. STATE FEEDBACK CONTROLLER.;250
34.8;8. CONCLUSION;252
34.9;9. REFERENCES;253
35;CHAPTER 38. MULTIPLE STEADY STATES IN AZEOTROPIC DISTILLATION AND THEIR EFFECT ON COLUMN OPERATION AND DESIGN;254
35.1;1. INTRODUCTION;254
35.2;2. COLUMNS WITHOUT DECANTER;255
35.3;3. COLUMNS WITH DECANTER;256
35.4;4. FINITE REFLUX AND FINITE NUMBER OF TRAYS;257
35.5;5. CONCLUSIONS;258
35.6;6. REFERENCES;259
36;CHAPTER 39. COMPARISON OF THE SEPARATION PERFORMANCES OF A MULTI-EFFECT BATCH DISTILLATION SYSTEM AND A CONTINUOUS DISTILLATION SYSTEM;260
36.1;1. INTRODUCTION;260
36.2;2. MULTIPLE-EFFECT BATCH DISTILLATION SYSTEM;261
36.3;3. MATHEMATICAL MODEL OF MEBAD;261
36.4;4. COMPARISON OF THE SEPARATION PERFORMANCE OF MEBAD AND CONTINUOUS SYSTEM;262
36.5;5. CONTROL OF MEBAD;264
36.6;6. CONCLUSION;265
36.7;ACKNOWLEDGMENT;265
36.8;REFERENCES;265
37;CHAPTER 40. ANALYSIS AND DESIGN OF CASCADE CONTROL SCHEMES FOR DISTILLATION;266
37.1;1. INTRODUCTION;266
37.2;2. INTERACTIONS IN MULTIVARIABLE SYSTEMS WITH CASCADE CONTROL;266
37.3;3. PARAMETERS FOR THE SELECTION OF THE CASCADE;267
37.4;4. APPLICATIONS TO DISTILLATION COLUMNS;269
37.5;5. CONCLUSION;271
37.6;6. REFERENCES;271
38;CHAPTER 41. Evaluation of Dynamic Models of Distillation Columns with Emphasis on the Initial Response;272
38.1;1. Introduction;272
38.2;2. Tray Modeling;272
38.3;3. Linear Tray Hydraulics;273
38.4;4. Obtaining parameters from experiments;275
38.5;5. Results;275
38.6;6. Discussion and Conclusion;277
38.7;REFERENCES;278
39;CHAPTER 42. Plantwide Control Problem For a Process With Three Distillation Columns and Two Recycle Streams;280
39.1;1. INTRODUCTION;280
39.2;2. PLANTWIDE CONTROL PROBLEM;281
39.3;3. CONCLUSIONS;282
39.4;REFERENCES;283
39.5;NOTE;283
40;CHAPTER 43. WAVE-NET BASED ON-LINE QUALITY INFERENCE SYSTEM FOR POLYMERIZATION PROCESSES;286
40.1;1. INTRODUCTION;286
40.2;2. PROCESS AND DATA DESCRIPTION;287
40.3;3. MODELS FOR MI PREDICTION;287
40.4;4. FORMATION OF ADAPTIVE LEARNING FROM THE INFREQUENTLY MEASURED MI DATA;289
40.5;5. APPLICATION RESULTS;290
40.6;6. CONCLUSION;291
40.7;REFERENCES;291
41;CHAPTER 44. STATE AND PARAMETER ESTIMATION WITH AUGMENTED KALMAN FILTER APPLIED TO AN INDUSTRIAL POLYMER REACTOR;292
41.1;1. INTRODUCTION;292
41.2;2. MODEL OF THE COPOLYMER REACTOR;292
41.3;3. MODEL IDENTIFICATION;294
41.4;4. CONCLUSION;295
41.5;5. REFERENCES;295
42;CHAPTER 45. KALMAN FILTER AND NEURAL NETWORK FOR ON-LINE ESTIMATION OF POLYMER CHAIN CHARACTERISTICS;298
42.1;1. INTRODUCTION;298
42.2;2. DESCRIPTION OF THE PROCESS;299
42.3;3. KALMAN FILTERING WITH ANALYTIC MODEL;300
42.4;4. KALMAN FILTERING WITH NEURAL NETWORK MODELS;300
42.5;5. EXPERIMENTAL RESULTS;302
42.6;6. CONCLUSION;303
42.7;7. NOMENCLATURE;303
42.8;8. REFERENCES;303
42.9;9. APPENDIX;303
43;CHAPTER 46. INTERACTIONS BETWEEN PRODUCTION RATE OPTIMIZATION AND TEMPERATURE CONTROL IN GAS PHASE POLYETHYLENE REACTORS;304
43.1;1. INTRODUCTION;304
43.2;2. SYSTEM MODEL;305
43.3;3. FEEDBACK TEMPERATURE CONTROL;306
43.4;4. HANDLING CONTROL SATURATION;306
43.5;5. SIMULATION RESULTS AND DISCUSSION;307
43.6;6. CONCLUSIONS;308
43.7;7. REFERENCES;308
43.8;8. GLOSSARY;308
44;CHAPTER 47. CONTROLLABILITY ISSUES CONCERNING PARTICLE SIZE IN EMULSION POLYMERIZATION;310
44.1;1. INTRODUCTION;310
44.2;2. COMPETITIVE GROWTH FRAMEWORK;310
44.3;3. DYNAMIC COMPETITIVE GROWTH MODEL;311
44.4;4. COMPETITIVE GROWTH SIMULATIONS;312
44.5;5. GROWTH MECHANISM CONTROLLABILITY;312
44.6;6. CONCLUSIONS;315
44.7;7. NOMENCLATURE;315
44.8;8. REFERENCES;315
45;CHAPTER 48. MULTIVARIABLE CONTROL OF A CONTINUOUS CRYSTALLIZATION PROCESS USING EXPERIMENTAL INPUT-OUTPUT MODELS;316
45.1;1. INTRODUCTION;316
45.2;2. PROCESS DESCRIPTION;317
45.3;3. PROCESS DYNAMICS;317
45.4;4. Design of a stabilizing controller;317
45.5;5. Closed-loop MIMO identification;318
45.6;6. Controllability analysis;319
45.7;7. MPC control;319
45.8;8. Open-loop experimental process responses;320
45.9;9. Evaluation of the MPC controller;320
45.10;10. CONCLUSIONS;320
45.11;11. REFERENCES;321
46;CHAPTER 49. A DYNAMIC MODEL OF A SUPERFRACTIONATOR: A TEST CASE FOR COMPARING DISTILLATION CONTROL TECHNIQUES;322
46.1;INTRODUCTION;322
46.2;MODEL DESCRIPTION;322
46.3;TEST SCENARIOS;323
46.4;CONTROLLER TEST RESULTS;323
46.5;CONCLUSIONS;323
46.6;REFERENCES;324
47;CHAPTER 50. IDENTIFICATION FOR CONTROL OF HIGH-PURITY DISTILLATION COLUMNS - A BENCHMARK PROBLEM;328
47.1;1. INTRODUCTION;328
47.2;2. A BRIEF REVIEW;329
47.3;3. PROBLEM DESCRIPTION;330
47.4;4. MISO-IDENTIFICATION USING AN ARMAX-TYPE MODEL;331
47.5;5. CONCLUSIONS;333
47.6;FURTHER INFORMATION;333
47.7;REFERENCES;333
48;CHAPTER 51. DISTILLATION COLUMN CONTROL BENCHMARKS: Four Typical Problems;334
48.1;1. INTRODUCTION;334
48.2;2. PLANT DESCRIPTION;334
48.3;3. BENCHMARK PROBLEMS;335
48.4;4. OPERATING CONDITIONS;335
48.5;5. REFERENCES;336
49;CHAPTER 52. THE IMPACT OF PROCESS DIRECTIONALITY ON ROBUST CONTROL IN NON-IDEAL DISTILLATION;338
49.1;1. INTRODUCTION;338
49.2;2. DIRECTIONALITY;339
49.3;3. ROBUSTNESS;339
49.4;4. DIRECTIONALITY IN DISTILLATION;339
49.5;5. CONTROLLER DESIGN;341
49.6;6. CONCLUSIONS;342
49.7;7. ACKNOWLEDGMENTS;343
49.8;8. REFERENCES;343
50;CHAPTER 53. ROBUST ANALYSIS OF DISTILLATION COLUMN DYNAMICS;344
50.1;1. INTRODUCTION;344
50.2;2. DYNAMIC MODEL OF THE DISTILLATION COLUMN;345
50.3;3. UNCERTAINTY MODELING;346
50.4;4. ROBUST ANALYSIS TOOLS;347
50.5;5. ROBUST ANALYSIS OF THE DISTILLATION COLUMN DYNAMICS;348
50.6;6. CONCLUSION;349
50.7;7. REFERENCES;349
51;CHAPTER 54. INVESTIGATION OF OPERABILITY AND CONTROLLABILITY PROPERTIES OF A PILOT-SCALE DISTILLATION COLUMN;350
51.1;1. INTRODUCTION;350
51.2;2. DISTILLATION COLUMN SIMULATOR;351
51.3;3. OPERABILITY AND CONTROLLABILITY STUDY;351
51.4;4. EXPERIMENTAL VERIFICATION;355
51.5;5. CONCLUSION;355
51.6;ACKNOWLEDGEMENT;355
51.7;REFERENCES;355
52;CHAPTER 55. CONTROL OF CHEMICAL REACTORS USING MULTIPLE-MODEL ADAPTIVE CONTROL (MMAC);356
52.1;1. INTRODUCTION;356
52.2;2. IDENTIFICATION AND CONTROL WEIGHTING;357
52.3;3. EXAMPLE 1. INPUT MULTIPLICITIES;357
52.4;4. EXAMPLE 2. OUTPUT MULTIPLICITIES;358
52.5;5. SUMMARY AND CURRENT WORK;359
52.6;REFERENCES;359
53;CHAPTER 56. FLEXIBILITY ANALYSIS OF DYNAMIC CHEMICAL PROCESSES;362
53.1;1. INTRODUCTION;362
53.2;2. DYNAMIC FEASIBILITY/FLEXIBILITY ANALYSIS;363
53.3;3. FEASIBILITY/FLEXIBILITY ANALYSIS WITH GIVEN UNCERTAINTY PROFILE;364
53.4;4. EXAMPLE;364
53.5;5. CONCLUDING REMARKS;366
53.6;6. REFERENCES;366
54;CHAPTER 57. CONTROL OF A BATCH REACTOR USING A MULTIVARIATE STATISTICAL CONTROLLER DESIGN;368
54.1;1. INTRODUCTION;368
54.2;2. MPCA METHOD;369
54.3;3. PROCESS DESCRIPTION;369
54.4;4. Controller Formulation;370
54.5;5. SIMULATION RESULTS & DISCUSSION;371
54.6;6. REFERENCES;371
55;CHAPTER 58. INTEGRATION OF PROCESS AND CONTROL DESIGNS BY NONLINEAR GEOMETRIC METHODS;374
55.1;1. INTRODUCTION;374
55.2;2. THE CLASS OF PLANTS AND THE PROCESSCONTROL PROBLEM;375
55.3;3. SOLVABILITY OF THE PROCESS-CONTROL PROBLEM;375
55.4;4. APPLICATION EXAMPLE: A SEMIBATCH EMULSION POLYMERIZATION REACTOR;376
55.5;5. CONCLUSIONS;378
55.6;REFERENCES;378
55.7;APPENDIX;379
56;CHAPTER 59. DYNAMIC HEAT BALANCE MODEL FOR INDUSTRIAL BATCH REACTORS AND ITS APPLICATIONS;380
56.1;1. INTRODUCTION;380
56.2;2. GENERIC DYNAMIC HEAT BALANCE MODEL;381
56.3;3. APPLICATION TO A PBL REACTOR;382
56.4;4. APPLICATION TO AN EPS BATCH POLYMERIZATION REACTOR;383
56.5;5. CONCLUSIONS;384
56.6;ACKNOWLEDGEMENT;384
56.7;REFERENCES;384
57;CHAPTER 60. METHODS OF DUALITY IN PROBLEMS ABOUT EXPENDIENCY OF USAGE AND OPTIMIZATION OF CYCLIC REGIMES OF TECHNOLOGICAL PROCESSES.;386
57.1;1. INTRODUCTION.;386
57.2;2. OPTIMIZATION OP CYCLIC PROCESSES AND AVERAGING PROBLEMS OF MATHEMATICAL PROGRAMMING.;386
57.3;3. RESULTS OF USING DUAL METHODS FOR SOME PROCESSES.;388
57.4;4. ABSORPTION-ADSORPTION CYCLE.;389
57.5;5. CONCLUSION.;390
57.6;6. ACKNOWLEDGEMENTS.;390
57.7;REFERENCES.;390
58;CHAPTER 61. STATUS AND CHALLENGES OF INTELLIGENT PLANT CONTROL;392
58.1;1. INTRODUCTION;392
58.2;2. A STATUS OF AI APPLICATIONS IN CONTROL;395
58.3;3. AI RESEARCH IN MODELING;399
58.4;4. MODELING PROBLEMS IN PLANT CONTROL;399
58.5;5. MODELLING PLANT GOALS AND FUNCTIONS;403
58.6;6. CONCLUSIONS;409
58.7;7. REFERENCES;409
59;CHAPTER 62. Risk-Conscious Operation of Batch Processes;412
59.1;1. Introduction;412
59.2;2. Proposed Approach;412
59.3;3. A Simple Demonstration Example;413
59.4;4. A Structural Mismatch Example;415
59.5;5. Discussion;416
59.6;6. REFERENCES;416
60;CHAPTER 63. SYNTHESIS OF PROCEDURAL CONTROLLERS FOR BATCH CHEMICAL PROCESSES;418
60.1;1. INTRODUCTION;418
60.2;2. PRELIMINARY DEFINITIONS AND NOTATION;419
60.3;3. SUPERVISORY CONTROL THEORY;419
60.4;4. EXAMPLE;420
60.5;5. NOTIONS OF PROCEDURAL CONTROL;421
60.6;6. THE EXAMPLE REVISITED;422
60.7;7. SYNTHESIS PROCEDURE;423
60.8;8. CONCLUSION;423
60.9;9. REFERENCES;423
61;CHAPTER 64. TEMPERATURE CONTROL OF A BATCH ESTERIFICATION REACTOR OVERCOMING NON-LINEARITIES USING ADAPTIVE GAIN;424
61.1;1. PROBLEM STATEMENT;424
61.2;2. DIRECT CONTROLLER;425
61.3;3. MASTER-SLAVE CONTROL STRUCTURE;425
61.4;4. GAIN SCHEDULING;426
61.5;5. SPLIT RANGE CONTROL;428
61.6;6. IMPLEMENTATION RESULTS;429
61.7;7. REFERENCES;429
62;CHAPTER 65. TEMPERATURE CONTROL OF A BATCH REACTOR BY ON-LINE IDENTIFICATION OF A VAPOR PRESSURE LAW;430
62.1;1. INTRODUCTION;430
62.2;2. PROCESS OPERATION AND MODEL DESCRIPTION;431
62.3;3. ON-LINE IDENTIFICATION OF A VAPOR PRESSURE LAW;431
62.4;4. THERMAL CONTROL TROUGH PRESSURE BY ON-LINE IDENTIFICATION OF A VAPOR PRESSURE LAW;433
62.5;5. CONCLUSIONS;435
62.6;ACKNOWLEDGEMENTS;435
62.7;REFERENCES;435
63;CHAPTER 66. EFFECT OF MODEL UNCERTAINTY ON THE TENDENCY MODELING, OPTIMIZATION AND CONTROL OF BATCH REACTORS;436
63.1;1. INTRODUCTION;436
63.2;2. TENDENCY MODELING, OPTIMIZATION AND CONTROL;436
63.3;3. RESULTS;438
63.4;4. CONCLUSIONS;442
63.5;5. REFERENCES;442
64;CHAPTER 67. Nonlinear Inferential Parallel Cascade Control;444
64.1;INTRODUCTION;444
64.2;NONLINEAR INFERENTIAL PARALLEL CASCADE CONTROL (NIPCC);445
64.3;ILLUSTRATION OF NIPCC;446
64.4;CONCLUSIONS;449
64.5;REFERENCES;449
65;CHAPTER 68. NONLINEAR OBSERVER DESIGN WITH APPLICATION TO CHEMICAL REACTORS;450
65.1;1. INTRODUCTION;450
65.2;2. PRELIMINARIES;451
65.3;3. NONLINEAR OBSERVER DESIGN APPROACH;452
65.4;4. APPLICATION TO CHEMICAL REACTORS;453
65.5;5. CONCLUSIONS;455
65.6;6. ACKNOWLEDGMENT;455
65.7;7. REFERENCES;455
66;CHAPTER 69. pH CONTROL IN THE PRESENCE OF PRECIPITATION EQUILIBRIA;456
66.1;1. INTRODUCTION;456
66.2;2. PRECIPITATION EQUILIBRIA;456
66.3;3. PRECIPITATION IN THE PRESENCE OF ACIDS AND BASES;457
66.4;4. A DYNAMIC MODEL FOR PRECIPITATION PROCESSES;458
66.5;5. CONTROL STRUCTURE;459
66.6;6. COMPUTER SIMULATIONS;460
66.7;8. REFERENCES;461
67;CHAPTER 70. PARTITIONING-SPACE APPROACH FOR NONLINEAR PROCESS CONTROL;462
67.1;1. INTRODUCTION;462
67.2;2. SYSTEM PARTITIONING;463
67.3;3. CONTROLLER DESIGN;464
67.4;4. APPLICATIONS;465
67.5;5. CONCLUSION;467
67.6;5. REFERENCES;467
68;CHAPTER 71. LIMITATIONS TO INPUT-OUTPUT ANALYSIS OF CASCADE CONTROL OF UNSTABLE CHEMICAL REACTORS;468
68.1;1. INTRODUCTION;468
68.2;2. CSTR MODELING EQUATIONS;468
68.3;3. CONTROL SYSTEM DESIGN;469
68.4;4. CONCLUSION;472
68.5;5. REFERENCES;472
68.6;APPENDIX;472
69;CHAPTER 72. AUTOMATIC CONTROL OF CHEMICAL REACTORS AT UNSTABLE STEADY-STATES;474
69.1;1. INTRODUCTION;474
69.2;2. TUNING TECHNIQUE;474
69.3;3. APPLICATIONS;476
69.4;4. LIMITS AND EXTENSIONS OF THE TUNING PROCEDURE;478
69.5;5. CONCLUSION;479
69.6;6. REFERENCES;479
70;CHAPTER 73. MULTIVARIABLE QUALITY CONTROL OF A CRUDE OIL FRACTIONATOR;480
70.1;INTRODUCTION;480
70.2;PROCESS DESCRIPTION;481
70.3;THE CRUDE FRACTIONATOR CONTROL PROBLEM;481
70.4;THE CONTROLLER EQUATIONS;482
70.5;THE OPEN-LOOP DYNAMICS OF THE ATMOSPHERIC FRACTIONATOR;483
70.6;PLANT RESULTS;484
70.7;REFERENCES;485
70.8;CONCLUSION;485
71;CHAPTER 74. COMPOSITION ESTIMATORS FOR A DISTILLATION COLUMN: THEORY AND EXPERIMENTS;486
71.1;1. INTRODUCTION;486
71.2;2. THE MODELS;487
71.3;3. EXPERIMENTAL DATA;489
71.4;4. RESULTS AND DISCUSSION;489
71.5;5. CONCLUSION;490
71.6;ACKNOWLEDGMENTS;491
71.7;REFERENCES;491
72;CHAPTER 75. PREDICTION AND ANALYSIS OF THE EFFECT OF REBOILER AND CONDENSER HOLDUP ON THE DYNAMIC BEHAVIOUR OF DISTILLATION COLUMNS;492
72.1;1 INTRODUCTION;492
72.2;2. THE RIGOROUS MODEL;493
72.3;3. THE PROPOSED SIMPLIFIED METHOD;493
72.4;4 "DECOUPLED" COLUMNS;494
72.5;5. INTERNAL FLOW CHANGES;495
72.6;6. TIME CONSTANT PREDICTION WITH "NON ACTIVE" HOLD-UPS;496
72.7;7 ANALYSIS OF THE RESULTS OBTAINED WITH THE PROPOSED METHOD;497
72.8;REFERENCES;498
73;CHAPTER 76. Development and Experimental Verification of a Simulation Tool for Column Startup;500
73.1;1. INTRODUCTION;500
73.2;2. SIMULATION MODEL;501
73.3;3. DESCRIPTION OF THE COLUMN;501
73.4;4. EXPERIMENTS;502
73.5;5. RESULTS;504
73.6;6. CONCLUSION;505
73.7;7. REFERENCES;505
73.8;8. NOMENCLATURE;505
74;CHAPTER 77. VERIFICATION OF A DISTILLATION COLUMN BENCHMARK;506
74.1;1. INTRODUCTION;506
74.2;2. PLANT DESCRIPTION;506
74.3;3. MODELLING ASSUMPTIONS;507
74.4;4. VALIDATION;508
74.5;5. CONCLUSIONS;511
74.6;6. REFERENCES;511
75;AUTHOR INDEX;512