Artificial Intelligence in Real-Time Control 1991 (eBook)

Front Cover 1
Artificial Intelligence in Real-Time Control 1991 4
Copyright Page 5
Table of Contents 10
Preface 8
PART 1: NEW PARADIGMS FOR AI IN REAL-TIME SYSTEMS 12
CHAPTER 1. TOWARDS DISTRIBUTED REAL-TIME INTELLIGENCE 12
INTRODUCTION 12
IDENTIFYING THE FUTURE REQUIREMENTS OF INTELLIGENT SYSTEMS 12
A DISTRIBUTED REAL-TIME INTELLIGENT FRAMEWORK 13
THE BULLETIN BOARD MODEL 15
CONCLUSIONS 16
REFERENCES 17
CHAPTER 2. ARTIFICIAL INTELLIGENCE IN HARD REAL-TIME - A 
20 
INTRODUCTION 20
DEDUCTION AND INDUCTION BASED METHODS IN CONVENTIONAL AI 20
HARD REAL-TIME SYSTEMS AND AI METHODS 21
A NEW PARADIGM FOR DEVELOPING AI METHODS FOR HARD REAL-TIME SYSTEMS 22
CONCLUSIONS 23
REFERENCES 23
PART 2: INTELLIGENT REAL-TIME CONTROL 24
CHAPTER 3. DICE: A FRAMEWORK FOR INTELLIGENT REAL-TIME 
24 
1 Introduction 24
2 Real-Time Expert Systems 24
3 DICE 25
4 Uncertainty management in DICE 27
5 Intelligent control 27
6 Application of DICE in Intelligent Control 27
7 Conclusions 29
References 29
CHAPTER 4. A REAL TIME EXPERT SYSTEM ENVIRONMENT FOR 
30 
1 INTRODUCTION 30
2 Global Architecture 30
3 Regulators 32
4 Implementation 33
5 Application 34
6 Conclusions and future work 35
Acknowledgments 35
References 35
CHAPTER 5. PREPROCESSING INPUTS FOR ADAPTIVE CRITIC CONTROL 38
INTRODUCTION 38
THE METHODS 39
SIMULATION RESULTS 41
ACKNOWLEDGEMENTS 42
REFERENCES 42
PART 3: TEMPORAL REASONING 44
CHAPTER 6. KNOWLEDGE-BASED REAL TIME CONTROL: THE USE OF ABSTRACTION TO SATISFY DEADLINES¹ 44
KNOWLEDGE-BASED REAL TIME CONTROL 44
MODELLING PHYSICAL SYSTEMS 45
PROCESSING PRIME AND DOMAIN MODELS 46
MODEL PROCESSING IN THE BBl ARCHITECTURE 47
GENERATING ABSTRACT MODELS 47
ON-LINE USE OF MODELS 49
EXAMPLES 49
CONCLUSIONS 51
REFERENCES 51
CHAPTER 7. MODEL-BASED DIAGNOSIS OF COMPLEX SYSTEMS: 
52 
INTRODUCTION 52
KNOWLEDGE REPRESENTATION 52
INFERENCE MECHANISM 54
CONCLUSION 55
REFERENCES 56
CHAPTER 8. EXPLICIT CLOCK TEMPORAL LOGIC IN CONSTRAINT 
58 
INTRODUCTION 58
EXPLICIT CLOCK TEMPORAL LOGIC 59
EXTERNAL CLOCKS AND TIMED BEHAVIORS 60
A CONSTRAINER FOR A REALTIME DATABASE 61
CONSISTENCY, INTEGRITY, AND KNOWLEDGEABILITY ISSUES 63
EXAMPLE CONTROLLER 66
CONCLUSION 67
REFERENCES 67
APPENDIX 69
PART 4: METHODOLOGY 70
CHAPTER 9. PLANNING FOR EMBEDDED SYSTEMS: 
70 
1 Introduction 70
2 Levels of Reactive Control 71
3 The TRA Model 71
4 TRA-based Specification 76
5 TRA-based Planning 77
6 Conclusion 78
References 78
CHAPTER 10. A UNIFIELD APPROXIMATE REASONING APPROACH FOR 
80 
INTRODUCTION 80
REASONING MODELS 80
RULE AGGREGATION 82
REASONING WITH SENSOR-BASED DATA 83
CONCLUDING REMARKS 84
REFERENCES 84
CHAPTER 11. USING ATMS ALGORITHMS FOR REAL-TIME APPLICATIONS 92
ABSTRACT 92
KEYWORDS 92
INTRODUCTION 92
1. ASSUMPTION-BASED TRUTH MAINTENANCE SYSTEMS 93
2· A TOY EXAMPLE IN LOGIC CIRCUITS 94
3. A REAL APPLICATION IN RAILWAY TRAFFIC CONTROL 95
CONCLUSIONS 96
Acknowledgements 96
REFERENCES 96
CHAPTER 12. SOFTWARE TOOLS FOR DISTRIBUTED INTELLIGENT 
98 
1. INTELLIGENT CONTROL TODAY 98
2. NEAR-TERM APPLICATIONS OF AI TO CONTROL ENGINEERING 98
3. COMPUTER-AIDED CONTROL ENGINEERING 99
4. WORKSHOP ON SOFTWARE TOOLS FOR DISTRIBUTED INTELLIGENT CONTROL 100
5. APPLYING THE RESULTS OF THE WORKSHOP 100
6. REFERENCES 100
CHAPTER 13. SEQUENTIAL FUNCTION CHARTS FOR KNOWLEDGE-BASED, REAL-TIME APPLICATIONS 102
1. Introduction 102
2. G2 103
3. Grafchart elements 103
4. Exceptions 105
5. Implementation 106
6. Applications 107
7.Conclusions 107
References 107
CHAPTER 14. PHASE SPACE NAVIGATOR: TOWARDS AUTOMATING 
 
108 
Abstract 108
1 Introduction 108
2 Automatic Control Synthesis in Phase Spaces 109
3 The Automated Control Synthesis Algorithm 110
4 An Example: Stabilizing a Buckling Column 112
5 Conclusions 113
References 113
CHAPTER 15. NATURAL LANGUAGE INTERFACE FOR 
114 
INTRODUCTION 114
NATURAL LANGUAGE INTERFACES 115
KNOWLEDGE BASE 115
DEVELOPED PROTOTYPE 117
APPLICATION EXAMPLES 117
CONCLUSIONS 119
ACKNOWLEDGEMENT 119
REFERENCES 119
CHAPTER 16. NEURAL-NET AUGMENTATION OF ADAPTIVE 
120 
INTRODUCTION 120
APPROACH 121
RESULTS 121
SUMMARIZING COMMENTS 123
REFERENCES 124
CHAPTER 17. KNOWLEDGE REPRESENTATION FOR REAL-TIME ON-LINE 
126 
INTRODUCTION 126
KNOWLEDGE REPRESENTATION AND ACQUISITION 126
KNOWLEDGE REPRESENTATION AND REASONING 127
AN EXPERIMENT IN ON-LINE INSPECTION 129
CONCLUSION 129
REFERENCES 129
PART 5: QUALITATIVE REASONING 132
CHAPTER 18. MODELBASED ALARM ANALYSIS USING MFM 132
Abstract 132
An Introduction to MFM 132
The Basic Flow Functions 133
Connection of Flow Functions 133
Failure Conditions for Flow Functions 133
A Method for Alarm Analysis 134
Possible Secondary Alarms 134
Unknown Alarm States 135
Measurement Errors 135
Generation of Alarms 135
An MFM Toolbox in G2 136
An Example—The Tanks Process 136
Experimental Experiences 137
Conclusions 137
Acknowledgements 137
References 137
CHAPTER 19. STRUCTURAL ESTIMATION WITH THE HYBRID 
138 
INTRODUCTION 138
THREE KINDS OF STRUCTURE 138
THE HYBRID PHENOMENA THEORY 139
STRUCTURAL ESTIMATION 142
CONCLUSION AND FUTURE WORK 143
REFERENCES 143
CHAPTER 20. METHOD OF INDUCING RULES FOR FUZZY CONTROLLERS 144
INTRODUCTION 144
RULE INDUCTION METHOD 145
SYSTEM IMPLEMENTATION: FUZZY CONTROL SYNTHESIZED SOFTWARE (FCSS) 145
APPLICATIONS 146
ACKNOWLEDGMENTS 149
REFERENCES 149
PART 6: APPLICATIONS 150
CHAPTER 21. RECOVERY BOILER INTELLIGENT CONTROL 150
INTRODUCTION 150
RECOVERY BOILER PLANT 150
GENERAL CONCEPTS OF THE SYSTEM 151
DETAILED DESCRIPTION OF THE CONTROL ALGORITHM 151
SIMULATIONS 154
CONCLUSION 154
REFERENCES 154
CHAPTER 22. FLANEX - A FLOW LINE ANALYZING EXPERT SYSTEM 156
INTRODUCTION 156
SYSTEM DESCRIPTION 156
ANALYSE - THE ANALYZING SUBSYSTEM OF FLANEX 157
THE USER INTERFACE ELIAS 158
CONCLUSION 159
REFERENCES 159
ACKNOWLEDGEMENTS 159
CHAPTER 23. APPLICATIONS OF INTELLIGENT TELEROBOTIC 
160 
INTRODUCTION 160
TELEROBOTICS APPLICATIONS LABORATORY 160
WASTE SORTING 161
SUMMARY AND CONCLUSIONS 161
REFERENCES 161
CHAPTER 24. SLAB REHEATING FURNACE TEMPERATURE CONTROL 
164 
INTRODUCTION 164
PROBLEMS OF CONVENTIONAL ACC 165
PURPOSE OF INTRODUCTION OF AI 165
CONFIGURATION OF SYSTEM 165
EVALUATION 166
TOOL FOR REALTIME AI 166
CONCLUSION 168
REFERENCES 168
CHAPTER 25. PROCESS CONTROL SYSTEM FOR BLAST FURNACE 
170 
INTRODUCTION 170
OUTLINE OF THE EXPERT SYSTEM 171
FURNACE CONDITION INFERENCE PROCESS 171
THE KNOWLEDGE MODEL 172
ADAPTIVE IDENTIFICATION MODEL 173
APPLICATION 173
CONCLUSION 174
REFERENCES 174
AUTHOR INDEX 176
KEYWORD INDEX 178