Fleming / Kwon Algorithms and Architectures for Real-Time Control 1992

1. Auflage 2014
ISBN: 978-1-4832-9793-4
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 363 Seiten, Web PDF

Reihe: IFAC Postprint Volume

This Workshop focuses on such issues as control algorithms which are suitable for real-time use, computer architectures which are suitable for real-time control algorithms, and applications for real-time control issues in the areas of parallel algorithms, multiprocessor systems, neural networks, fault-tolerance systems, real-time robot control identification, real-time filtering algorithms, control algorithms, fuzzy control, adaptive and self-tuning control, and real-time control applications.

Autoren/Hrsg.

Fleming, P. J.

Kwon, W. H.

Inhaltsverzeichnis

1;Front Cover;1
2;Algorithms and Architectures for Real-Time Control;2
3;Copyright Page;3
4;Table of Contents;6
5;IFAC Workshop on Algorithms and Architectures for Real-Time Control;4
6;Preface;5
7;CHAPTER 1. CONTEMPORARY COMPUTERS CONSIDERED INAPPROPRIATE FOR REAL TIME CONTROL;12
7.1;INTRODUCTION;12
7.2;REAL TIME REQUIREMENTS;13
7.3;UNPREDICTABLE BEHAVIOUR;13
7.4;DATA CONVERSIONS;14
7.5;INHERENT DELAYS;14
7.6;MULTI-VARIABLE CONTROL;15
7.7;TIME;16
7.8;INAPPROPRIATE PRACTICE;16
7.9;SAFETY CRITICAL CONTROL;17
7.10;A PERSPECTIVE FOR THE FUTURE DEVELOPMENT;17
7.11;REFERENCES;19
8;CHAPTER 2. HARD DEADLINES IN REAL-TIME CONTROL SYSTEMS;20
8.1;1 Introduction;20
8.2;2 The Effects of Controller Computer Failures;21
8.3;3 Derivation of Hard Deadlines;21
8.4;4 Examples;24
8.5;5 Application of Hard Deadline Information;24
8.6;6 Conclusion;25
8.7;Acknowledgement:;25
8.8;References;25
9;CHAPTER 3. PARALLEL ALGORITHMS FOR CONTROL;26
9.1;INTRODUCTION;26
9.2;SYSTOLIC ALGORITHMS FOR MATRIX CALCULATIONS;27
9.3;SYSTOLIC ALGORITHMS FOR DISCRETE KALMAN FILTERING;27
9.4;ALGORITHM ENGINEERING;28
9.5;TRANSPUTER IMPLEMENTATIONS;29
9.6;PARALLEL KALMAN-BUCY FILTERING;29
9.7;DISCUSSION AND CONCLUSIONS;30
9.8;REFERENCES;30
10;CHAPTER 4. PARALLEL ALGORITHMS FOR THE QUASI-TRIANGULAR GENERALIZED SYLVESTER MATRIX EQUATION ON A SHARED MEMORY MULTIPROCESSOR;34
10.1;1. INTRODUCTION;34
10.2;2. SOLUTION OF THE TRIANGULAR GENERALIZED SYLVESTER EQUATION;35
10.3;3. SOLUTION OF THE QUASI-TRIANGULAR GENERALIZED SYLVESTER EQUATION;36
10.4;4. ALLIANT FX/80 IMPLEMENTATION;38
10.5;5. CONCLUSIONS;38
10.6;References;39
11;CHAPTER 5. A SYSTOLIC ALGORITHM FOR THE TRIANGULAR SYLVESTER EQUATION IN A LINEAR ARRAY;40
11.1;INTRODUCTION;40
11.2;TRIANGULAR FORM OF SYLVESTER EQUATION;40
11.3;SYSTOLIC ALGORITHM FOR THE TRIANGULAR SYLVESTER EQUATION;40
11.4;SIZE-DEPENDENT BIDIMENSIONAL ARRAY;41
11.5;SIZE-INDEPENDENT BIDIMENSIONAL ARRAY;41
11.6;SIZE-DEPENDENT LINEAR ARRAY;42
11.7;SIZE-INDEPENDENT LINEAR ARRAY;42
11.8;CONCLUSION;43
11.9;REFERENCES;43
12;Chapter 6. Real Time Control of a Multiple Arm System by Large Scale Multiprocessing;48
12.1;INTRODUCTION;48
12.2;TRANSPUTER FAMILY;48
12.3;PERIPHERAL INTERFACE;49
12.4;OCCAM/TDS;50
12.5;WELL STRUCTURED SYSTEM SOFTWARE;51
12.6;APPLICATION TO ROBOT SYSTEM CONTROL;53
12.7;CONCLUDING REMARKS;53
12.8;ACKNOWLEDGMENT;53
12.9;REFERENCES;53
13;CHAPTER 7. A MODULAR, MASSIVELY PARALLEL COMPUTER ARCHITECTURE FOR TRAINABLE REAL-TIME CONTROL SYSTEMS;54
13.1;INTRODUCTION;54
13.2;SYSTEM ARCHITECTURE: THE CONCEPT;54
13.3;SYSTEM ARCHITECTURE: IMPLEMENTATION;56
13.4;SYSTEM DEVELOPMENT: IMPLEMENTATION;57
13.5;DISCUSSION AND CONCLUSION;59
13.6;REFERENCES;59
14;CHAPTER 8. PARALLELIZED INVERSE DYNAMICS ALGORITHM FOR DYNAMIC CONTROL OF A ROBOT MANIPULATOR;60
14.1;INTRODUCTION;60
14.2;ROBOT INVERSE DYNAMICS;60
14.3;PARALLELIZATION OF ROBOT INVERSE DYNAMICS;61
14.4;TRANSPUTER AND PARALLEL PROCESSING SYSTEM;63
14.5;EXPERIMENTAL RESULT;63
14.6;CONCLUSION AND FURTHER STUDIES;64
14.7;REFERENCE;64
15;CHAPTER 9. ROBOT POSITION CONTROL BASED ON A TRANSPUTER NETWORK WITH A CONTACTLESS SENSOR;66
15.1;Introduction;66
15.2;Control Architecture;66
15.3;Transputer Network;67
15.4;Sensor System;68
15.5;Results;69
15.6;References;71
16;CHAPTER 10. A TRANSPUTER-BASED CONTROLLER FOR THE RTX ROBOT;72
16.1;Abstract;72
16.2;1 Introduction;72
16.3;2 The RTX Robot;73
16.4;3 The Transputer;73
16.5;4 The Interface — Hardware Aspects;73
16.6;5 The Interface - Software Aspects;74
16.7;6 Robot trajectory planning;74
16.8;7 Conclusions;76
16.9;References;76
17;Chapter 11. Implementation of Parallel Logic Solving Algorithmfor the PLC Based On Dataflow Architecture;78
17.1;INTRODUCTION;78
17.2;EVENT DRIVEN SEQUENCE CONTROL;79
17.3;LOGIC PROGRAMMING AND FORMALIZATION;79
17.4;OPERATION OF EVENT DRIVEN PLC;80
17.5;RUN TIME OPTIMIZATION ALGORITHM;81
17.6;ARCHITECTURE OF EVENT DRIVEN PLC;81
17.7;PERFORMANCE EVALUATION;82
17.8;CONCLUSION;83
17.9;REFERENCES;83
18;CHAPTER 12. AN ARCHITECTURE ENABLING THE SAFETY LICENSING OF REAL TIME CONTROLLERS;84
18.1;INTRODUCTION;84
18.2;A SOFTWARE ENGINEERING PARADIGM;86
18.3;THE ARCHITECTURAL CONCEPT;87
18.4;SOFTWARE LICENSING;90
18.5;CONCLUSION;91
18.6;REFERENCES;91
19;Chapter 13. Safe, Fault-Tolerant and Deterministic Algorithms for Real Time Control;92
19.1;Introduction;92
19.2;Parallel Processing in Control;92
19.3;Deterministic Timing Environments;92
19.4;The virtual programming environment.;93
19.5;The CpmmijniaitiQn Harness;93
19.6;High Reliability;95
19.7;Conclusions;97
19.8;References;97
20;chapter 14. Voting Software for Fault-Tolerant Aircraft Flight Control Systems;98
20.1;Abstract;98
20.2;1 Introduction;98
20.3;2 Background;99
20.4;3 Voting Algorithms;99
20.5;4 Intelligent Voter Experiments;101
20.6;5 Future Experimental Work;103
20.7;6 Conclusions;103
20.8;7 Acknowledgements;103
20.9;8 References;103
21;CHAPTER 15. A FAULT TOLERANT CONTROL SYSTEM FOR A HIGH PERFORMANCE INDUCTION MOTOR DRIVE;104
21.1;INTRODUCTION;104
21.2;COMPARISON OF FAULT-TOLERANT CONTROLLERS;104
21.3;THE SYSTEM ARCHITECTURE;105
21.4;THE ANALYSIS AND COMPARISON OF RELIABILITY;105
21.5;THE FAULT-TOLERANT TECHNIQUE;107
21.6;CONCLUSION;108
21.7;REFERENCE;108
22;Chapter 16. A Parallel Algorithm for Training Neural Network Based Nonlinear Models;110
22.1;INTRODUCTION;110
22.2;NEURAL NONLINEAR MODELLING;111
22.3;THE BFGS ALGORITHM;111
22.4;A PARALLEL BFGS ALGORITHM;112
22.5;CONCLUSIONS;115
22.6;ACKNOWLEDGEMENT;115
22.7;REFERENCES;115
23;Chapter 17. Review of Identification Techniques for Nonlinear Systems Using Neural Networks;116
23.1;Abstract;116
23.2;1 Introduction;116
23.3;2 Theoretical Background;116
23.4;3 Neural Networks Approach;118
23.5;4 Radial Basis Function Network;120
23.6;5 Conclusion;121
23.7;References;121
24;CHAPTER 18. OPTIMAL EDGE SELECTION BY THE MODIFIED GENETIC ALGORITHM;122
24.1;Abstract;122
24.2;1 Introduction;122
24.3;2 Neural Network Application;123
24.4;3 Conclusions;125
24.5;4 Future Work;125
24.6;References;125
25;CHAPTER 19. REAL-TIME FAULTS DIAGNOSIS IN A LARGE-SCALE SYSTEM USING NEURAL NETWORKS BASED ON SIGNED GAIN DIGRAPH WITH APPLICATION;128
25.1;INTRODUCTION;128
25.2;ASSUMPTIONS FOR FAULTS DIAGONSIS;129
25.3;PLANT STRUCTURE IDENTIFIER;129
25.4;PLANT DESCRIPTION;129
25.5;TRAINING DATA EXTRACTION FOR SUBSYSTEM;130
25.6;FAULTS DIAGONSIS;130
25.7;SIMULATION RESULTS;131
25.8;CONCLUSION;131
25.9;REFERENCES;133
26;CHAPTER 20. NEURAL NETWORK IMPLEMENTATION FOR REAL-TIME CLOSED-LOOP MOTION CONTROL OF REDUNDANT ROBOTS;134
26.1;ABSTRACT;134
26.2;I. INTRODUCTION;134
26.3;II. CONTROL SCHEME;135
26.4;III. NEURAL NET IMPLEMENTATION;135
26.5;V. EXPERIMENTAL RESULTS;136
26.6;VI. REAL-TIME TRAINING ALGORITHM;137
26.7;VII. CONCLUSION;137
26.8;REFERENCES;138
27;CHAPTER 21. SYSTEM IDENTIFICATON USING NEURAL NETWORKS;140
27.1;INTRODUCTION;140
27.2;SYSTEM IDENTIFICATION USING NEURAL NETWORKS;140
27.3;GAIN ADJUSTMENT OF I-PD CONTROL SYSTEM;143
27.4;CONCLUSIONS;144
27.5;ACKNOWLEDGMENTS;144
27.6;REFERENCES;145
28;CHAPTER 22. ARTIFICIAL NEURAL NETWORK APPROACH TO INFERENTIAL CONTROL OF VOLATILITY IN REFINERY PLANTS;146
28.1;INTRODUCTION;146
28.2;ARTIFICIAL NEURAL NETWORK;147
28.3;PREDICTION OF VOLATILITY;148
28.4;CONCLUSIONS;149
28.5;ACKNOWLEDGMENTS;149
28.6;REFERENCES;149
29;Chapter 23. On-Line Identification of State-Space Models via Exploitation of Displacement Structure;152
29.1;1 Introduction;152
29.2;2 A Conventional State Space Identification Method;153
29.3;3 A Fast State Space Model Identification: Recursive Processing;154
29.4;4 Simulations;156
29.5;5 Conclusions;157
29.6;REFERENCES;157
30;Chapter 24. Index Rule Scheduling Policies Applied To Identification;158
30.1;1 Introduction;158
30.2;2 Cost functions and sensorcontrol policies;159
30.3;3 Multi-armed bandit formulation and optimal solution;160
30.4;4 Convergence aspects;161
30.5;5 Efficient computation of the indices;161
30.6;6 Numerical simulations;162
30.7;REFERENCES;162
30.8;Appendix;162
31;CHAPTER 25. A CURVE-BROKEN-LINE METHOD FOR SYSTEM IDENTIFICATION;164
31.1;INTRODUCTION;164
31.2;ALGORITHM;167
31.3;EXAMPLE;168
31.4;CONCLUSION;169
31.5;APPENDIX;169
31.6;REFERENCES;169
32;CHAPTER 26. ROBUST FAILURE DETECTION AND ISOLATION IN NON-LINEAR CONTROL SYSTEMS;170
32.1;INTRODUCTION;170
32.2;PROBLEM FORMULATION;170
32.3;ROBUST REDUNDANCY RELATIONS;171
32.4;MATHEMATICAL TECHNIQUES;171
32.5;TRANSFORMATION OF INITIAL MODEL;172
32.6;OPTIMAL REDUNDANCY RELATIONS;173
32.7;DIAGNOSIS UNDER NOISE CONDITIONS;174
32.8;CONCLUSION;175
32.9;REFERENCES;175
33;CHAPTER 27. A NEW DYNAMIC NEUROCONTROL ARCHITECTURE FOR ROBOT MANIPULATORS;176
33.1;INTRODUCTION;176
33.2;THE PROPOSED NEUROCONTROL ARCHITECTURE;177
33.3;TRAINING THE PROPOSED NEUROCONTROLLER;177
33.4;DYNAMIC COMPUTER SIMULATION;178
33.5;CONCLUSION;180
33.6;REFERENCE;180
34;CHAPTER 28. A SIGNAL PROCESSOR BASED REAL- TIME CONTROL FOR A POSITION AND ORIENTATION MEASUREMENT SYSTEM FOR INDUSTRIAL ROBOTS;182
34.1;INTRODUCTION;182
34.2;REAL TIME CONTROLLER;185
34.3;CONCLUSION;186
34.4;ACKNOWLEDGEMENTS;186
34.5;REFERENCES;186
35;CHAPTER 29. ACCURACY INCREASING OF ROBOT REAL-TIME CONTROL;188
35.1;INTRODUCTION;188
35.2;WORKCELL CALIBRATION ALGORITHM;188
35.3;SOFTWARE FOR ROBOTIC CELL CALIBRATION;190
35.4;EXPERIMENTAL VERIFICATION;190
35.5;CONCLUSION;191
35.6;REFERENCES;191
36;CHAPTER 30. DESIGN OF A SIMPLE AND ROBUST CONTROL SYSTEM FOR A SINGLE-LINK FLEXIBLE ROBOT ARM;192
36.1;INTRODUCTION;192
36.2;DYNAMIC MODEL OF A FLEXIBLE ROBOT ARM;193
36.3;DESIGN OF A CONTROLLER;194
36.4;SIMULATION RESULTS;195
36.5;CONCLUSION;196
36.6;REFERENCES;196
37;CHAPTER 31. SUPPRESSION METHOD OF DISTURBANCE TORQUE DUE TO SYSTEM DRIFT VIA AN OBSERVER IN THE ROBOT CONTROL SYSTEM;198
37.1;INTRODUCTION;198
37.2;ESTIMATION OF THE SYSTEM DRIFT;200
37.3;CONCLUSION;202
37.4;REFERENCES;202
38;CHAPTER 32. AN EXTENDED WORKSPACE MAPPING ALGORITHM AND ITS IMPLEMENTATION IN A NUCLEAR TELE-ROBOTIC CONTROL SYSTEM;204
38.1;INTRODUCTION;204
38.2;EXTENDED WORKSPACE MAPPING;205
38.3;MASTER-SLAVE MANIPULATOR SYSTEM HARDWARE;205
38.4;KINEMATIC ANALYSIS OF THE MASTER-SLAVE SYSTEM;206
38.5;PROPOSED EXTENDED WORKSPACE MAPPING METHODS;207
38.6;PHYSICAL IMPLEMENTATIONS OF THE MAPPING ALGORITHM;208
38.7;CONCLUSION;208
38.8;REFERENCES;208
39;CHAPTER 33. REAL-TIME ALGORITHM OF THE INVERSE DYNAMICS OF FLEXIBLE ARMS;210
39.1;INTRODUCTION;210
39.2;PRELIMINARIES;210
39.3;REAL-TIME IMPLEMENTATION;213
39.4;NUMERICAL EXAMPLES;213
39.5;CONCLUSIONS;214
39.6;REFERENCES;214
40;CHAPTER 34. REAL-TIME NAVIGATION AND OBSTACLE AVOIDANCE BASED ON GRIDS METHOD FOR FAST MOBILE ROBOT;216
40.1;INTRODUCTION;216
40.2;CONTROL ALGORITHM;216
40.3;EXPERIMENTAL RESULTS;219
40.4;CONCLUSIONS;219
40.5;REFERENCES;220
41;CHAPTER 35. STRUCTURED MATRICES AND FAST RLS ADAPTIVE FILTERING;222
41.1;INTRODUCTION;222
41.2;SQUARE-ROOT CHANDRASEKHAR ALGORITHM;223
41.3;STRUCTURED TIME-VARIANT MODELS;223
41.4;CONNECTION TO THE SCHUR ALGORITHM;224
41.5;RECURSIVE LEAST-SQUARES;225
41.6;FAST RECURSIVE LEAST SQUARES;226
41.7;EXTENSIONS AND CONCLUDING REMARKS;227
41.8;REFERENCES;227
42;CHAPTER 36. DEVELOPMENT OF A TRACK-WHILE-SCAN FILTER WITH PSEUDOMEASUREMENTS;228
42.1;1. INTRODUCTION;228
42.2;2. TARGET DYNAMICS AND PSEUDOMEASUREMENTS;229
42.3;3. DEVELOPMENT OF A SUBOPTIMAL FILTER;230
42.4;4. A CONSTANT GAIN FILTER AND THE EKF;232
42.5;5. SIMULATION RESULTS AND CONCLUSIONS;233
42.6;REFERENCES;234
43;CHAPTER 37. A REDUCED ORDER EXTENDED KALMAN FILTER ALGORITHM FOR PARAMETER AND STATE ESTIMATION OF AN INDUCTION MOTOR;236
43.1;INTRODUCTION;236
43.2;KALMAN FILTERING;237
43.3;INDUCTION MOTOR MODELS;238
43.4;REDUCED ORDER EXTENDED KALMAN FILTER (REKF);239
43.5;SIMULATION RESULTS;240
43.6;CONCLUSIONS;241
43.7;AKNOWLEDGEMENTS;241
43.8;REFERENCES;241
44;CHAPTER 38. ON STOCHASTIC LYAPUNOV FUNCTION METHOD IN OPTIMAL LINEAR FILTERING PROBLEM;242
44.1;INTRODUCTION. PROBLEM STATEMENT;242
44.2;II. PRELIMINERY RESULTS;242
44.3;III. DESIGN OF STABLE FILTER FOR SYSTEM STATE;243
44.4;IV. SOME PROPERTIES OF STABLE FILTER;244
44.5;V. EXAMPLES;245
44.6;VI. CONCLUSION;245
44.7;APPENDIX;245
44.8;REFERENCES;246
45;Chapter 39. Specification of Intelligent Controllers for Discrete Event Systems in A Temporal Logic Framework;248
45.1;1 Introduction;248
45.2;2 Temporal Logic Models;249
45.3;3 Intelligent Controller Specification;250
45.4;4 Conclusions;252
45.5;References;252
46;CHAPTER 40. A NEW DECOMPOSITION METHOD OF RELATION MATRICES OF MULTTV ARIABLE FUZZY SYSTEMS;254
46.1;INTRODUCTION;254
46.2;OUTPUT INFERENCE FROM TWO-DIMENSIONAL RELATION MATRICES;254
46.3;A NEW DECOMPOSITION METHOD OF RELATION MATRICES;256
46.4;CONCLUSION;258
46.5;REFERENCES;258
47;Chapter 41. Identif icaion of Fuzzy Control Rules Utilizing GeneticAlgorithms and Its Application to Mobile Robot;260
48;INTRODUCTION;260
49;FUZZY IMPLICATION AND REASONING;261
50;STRUCTURE IDENTIFICATION;261
51;PARAMETER IDENTIFICATION;261
52;SIMULATION;262
53;CONCLUSION;264
54;ACKNOWLEDGEMENTS;264
55;REFERENCE;264
56;CHAPTER 42. CONTROL O F FED-BATCH FERMENTATIONPROCESS USING A SELF-ORGANIZINGFUZZY CONTROLLER;266
56.1;INTRODUCTION;266
56.2;SELF-ORGANIZING FUZZY CONTROLLER;266
56.3;APPLICATION TO FED-BATCH LYSINE FERMENTATION;268
56.4;RESULSTS AND DISCUSSIONS;268
56.5;CONCLUSIONS;269
56.6;ACKNOWLEDGMENT;270
56.7;REFERENCES;270
57;CHAPTER 43. PARALLEL ADAPTIVE CONTROL FOR TURBOGENERATOR SYSTEMS;272
57.1;INTRODUCTION;272
57.2;MEASUREMENT SYSTEM;273
57.3;SELF-TUNING CONTROL;273
57.4;TEST RESULTS;274
57.5;DISCUSSION AND CONCLUSIONS;276
57.6;REFERENCES;276
58;CHAPTER 44. EXPERT AUTO-TUNER FOR MULTIVARIABLE CONTROL APPLICATIONS;278
58.1;Abstract;278
58.2;1 INTRODUCTION;278
58.3;2 TERMINOLOGY;278
58.4;3 THE PROPOSED METHODOLOGY;279
58.5;4 PROCESS IDENTIFICATION;279
58.6;5 ESTIMATION OF DETUNING FACTOR;280
58.7;6 ON-LINE IDENTIFICATION OF THE RDG;280
58.8;7 IMPLEMENTATION AND RESULTS;281
58.9;8 AN APPLICATION EXAMPLE;282
58.10;9 CONCLUSION;282
58.11;References;283
59;Chapter 45. An Intelligent Self-Tuning Controller And Its Application To Load/Pressure Control System;284
59.1;1. Introduction;284
59.2;2. ISTC algorithm;284
59.3;3· SYSTEM DESCRIPTION;287
59.4;4. SIMULATION RESULTS;287
59.5;5: SUMMARY AND CONCLUTIONS;288
59.6;References;289
60;CHAPTER 46. SYNTHESIS OF ADAPTIVE CONTROL SYSTEMS FOR ROBOTS;290
61;INTRODUCTION;290
62;THE CHOICE OF WAYS TO SOLVE SYNTHESIS PROBLEM;290
63;METHODS OF SYNTHESIS OF ADAPTIVE CONTROL SYSTEMS;291
64;SOLUTION OF INVERSE DYNAMIC TASK;294
65;DETERMINING THE INDIVIDUALCOMPONENTS OF MOMENT ACTIONS;294
66;CONCLUSION;295
67;REFERENCES;295
68;CHAPTER 47. A SIMPLIFIED ROBUST PREDICTIVE CONTROLLER IN THE PRESENCE OF EXOGENOUS BOUNDED DISTURBANCES;296
69;INTRODUCTION;296
70;TRIANGLE MODEL AND DESIGN OF EXTENDED HORIZON ADAPTIVE PREDICTIVE CONTROLLER;296
71;STABILITY AND CONVERGENCE ANALYSES;298
72;CONCLUSION;299
73;REFERENCE;299
74;Chapter 48. A Hybrid Method for Real-time Simulation of Continuous-time Bilinear Systems;300
74.1;INTRODUCTION;300
74.2;SOLUTION STRATEGY;300
74.3;ALGORITHM DESCRIPTION;301
74.4;ERROR ANALYSIS;302
74.5;NUMERICAL EXAMPLES;303
74.6;CONCLUSIONS;305
74.7;REFERENCES;305
75;CHAPTER 49. A STUDY ON THE MINIMAL-TTME CONTROL PROBLEM OF A QUANTIZED LINEAR DISCRETE SYSTEM WITH RATIONAL COEFFICIENTS;306
75.1;1. INTRODUCTION;306
75.2;2. MINIMAL - TIME CONTROL OF DISCRETE QUANTIZED LINEAR CONTROL SYSTEMS WITH RATIONAL COEFFICIENTS;306
76;CHAPTER 50. PREDICTIVE CONTROL OF SYSTEMS WITH MULTIPLEXED MEASUREMENTS;312
76.1;Abstract;312
76.2;1 Introduction;312
76.3;2 System Model;313
76.4;3 Predictive Control;313
76.5;4 Multiplexing Algorithm;314
76.6;5 Simulations;315
76.7;6 Conclusions;316
76.8;References;316
77;Chapter 51. Real-Time Expert Intelligent Control System REICS;318
77.1;INTRODUCTION;318
77.2;ARCHITECTURE AND KNOWLEDGE REPRESENTATION OF REICS;318
77.3;INFERENCE MECHANISM OF REICS;320
77.4;SYSTEM SIMULATION & APPLICATION;322
77.5;CONCLUDING REMARK;323
77.6;REFERENCES;323
78;Chapter 52. Control Environment Implementation Issues- with Case Studies;324
78.1;Introduction;324
78.2;Case Studies;327
78.3;Conclusions;329
78.4;References;329
79;CHAPTER 53. REAL-TIME CELL CONTROL FOR FLEXIBLE MANUFACTURING;330
79.1;INTRODUCTION;330
79.2;THE UniSet ENVIRONMENT;331
79.3;OBJECT ORIENTED CELL REPRESENTATION APPROACH;332
79.4;TASK INITIATION DIAGRAMS;333
79.5;CONCLUSION;334
79.6;Reference;336
80;CHAPTER 54. THE DIGITAL CONTROL SYSTEM REALIZATION OFA SHORT RANGE SURFACE TO AIR MISSILE;338
80.1;INTRODUCTION;338
80.2;CONFIGURATION OF CONTROL SYSTEM;338
80.3;HARDWARE DESIGN AND IMPLEMENTATION;340
80.4;REAL TIME HILS;342
80.5;CONCLUSION;343
80.6;REFERENCE;343
81;Chapter 55. Continuation Method for Dynamic Economic Load Dispatch with Emission Constraints;344
81.1;INTRODUCTION;344
81.2;FORMULATION;344
81.3;CONTINUATION METHOD;345
81.4;CONCLUSIONS;348
81.5;REFERENCES;348
82;CHAPTER 56. REAL-TIME ARCHITECTURE OF AN ACTIVE NOISE ATTENUATION SYSTEM USING MICROPROCESSOR DSP96002;350
82.1;1. INTRODUCTION;350
82.2;2. ACTIVE NOISE ATTENUATION CONTROLLER;350
82.3;3. ROBUST RLS ALGORITHM;352
82.4;4. ALGORITHM OF AN ACTIVE NOISECONTROL SYSTEM;353
82.5;5. ARCHITECTURE OF AN ACTIVE NOISE ATTENUATION SYSTEM;353
82.6;6. EXPERIMENTAL RESULTS.;355
82.7;7. CONCLUSIONS;355
82.8;REFERENCE;355
83;CHAPTER 57. A STUDY ON NONLINEAR ROBUST ADAPTIVE CONTROL SYSTEM DESIGN OF INDUSTRIAL ROBOTIC MANIPULATOR;356
83.1;1. INTRODUCTION;356
83.2;2. DYNAMICS OF ROBOT MANIPULATOR;356
83.3;3. ROUBST ADAPTIVE CONTROL OF THE MANIPULATOR;357
83.4;4. SIMULATION;360
83.5;5.CONCLUSION;361
83.6;REFERENCE;361
84;CHAPTER 58. AN OBJECT-ORIENTED CONCEPTION OF A REAL-TIME CONTROL OF FMS;362
84.1;INTRODUCTION;362
84.2;THE DESIGN OF AN OBJECT DATA-BASE WITH A PROBLEM ORIENTATION TO FMS;362
84.3;PROCESS KNOWLEDGE RULES;364
84.4;PRODUCTION PLAN;365
84.5;EXPERT SYSTEM;365
84.6;TEMPORAL LOGIC AS AN ASSERTION LANGUAGE FOR SPECIFICATION OF SYSTEM'S BEHAVIOUR;366
84.7;CONCLUSIONS;368
84.8;REFERENCES;368
85;AUTHOR INDEX;370
86;KEYWORD INDEX;372