Application of Artificial Intelligence in Process Control (eBook)

Lecture Notes Erasmus Intensive Course

L. Boullart, A. Krijgsman, R. A. Vingerhoeds (Herausgeber)

eBook Download: PDF

2013 | 1. Auflage
544 Seiten
Elsevier Science (Verlag)
978-0-08-091263-9 (ISBN)

Infos

This book is the result of a united effort of six European universities to create an overall course on the appplication of artificial intelligence (AI) in process control. The book includes an introduction to key areas including; knowledge representation, expert, logic, fuzzy logic, neural network, and object oriented-based approaches in AI. Part two covers the application to control engineering, part three: Real-Time Issues, part four: CAD Systems and Expert Systems, part five: Intelligent Control and part six: Supervisory Control, Monitoring and Optimization.

Inhalt

Front Cover 1
Application of Artificial Intelligence in Process Control 4
Copyright Page 5
Table of Contents 6
Preface 10
Contributing authors 12
PART I: ARTIFICIAL INTELLIGENCE 14
Road Map 16
Chapter 1. A Gentle Introduction to Artificial Intelligence 18
1 Introduction 18
2 Definition of Artificial Intelligence 19
3 Application areas of A.I. 20
4 What is special on A.I. techniques? 23
5 Special Languages for A.I. 23
6 Expert Systems 36
7 Knowledge Representation and Extraction 39
8 Bibliography 44
Appendix A Rule based system called "CLIPS" 45
Chapter 2. Knowledge Representation by Logic 54
1 Introduction 54
2 Propositional Logic 56
3 The resolution of Propositional Logic Connectives 57
4 Predicate Logic 61
5 Unification in Predicate Logic 66
6 Conclusion 73
7 Bibliography 73
Chapter 3. Object Orientation and Object Oriented Programming 74
1 Introduction 74
2 Basic Principles of Object Orientation and Object Oriented Programming 75
3 Programming Example in Object Orientation 77
4 'Abstract Datatype' 83
5 Properties of Object Oriented Systems 84
6 Overloading of (internal) Primitive Methods 90
7 Conclusion 94
8 Bibliography 95
Chapter 4. Expert System Case Study: The Chocolate Biscuit Factory 97
1 Introduction 97
2 Knowledge representation 97
3 Knowledge elicitation 99
4 Forward Chaining 103
5 Backward Chaining 105
6 Control Strategy 106
7 Other Enhancements 106
8 Conclusions 108
Chapter 5. Using A.I.-Formalisms in Programmable Logic Controllers 109
1 Summary 109
2 Programmable Logic Controllers: state-of-the-art 109
3 Appreciation of the state-of-the-art PLC's 111
4 Using the PROLOG formalism in PLC's 111
5 Using Production Rules in PLC's. 122
6 Using Object-Oriented Programming in PLC's 126
7 Conclusion 126
Chapter 6. AN INTRODUCTION TO EXPERT SYSTEM DEVELOPMENT 127
1 The waterfall model 128
2 Rapid prototyping 129
3 The incremental development model 129
4 Kinds of knowledge 130
5 Knowledge acquisition techniques 131
6 Interacting with human experts 132
7 Record keeping 133
8 Introduction 134
9 Assessment and scoping 136
10 System specification 143
11 Incremental development 149
12 Final system integration and testing 152
13 System transference 152
14 Maintenance, enhancement and support 153
15 On the man-machine interface 154
16 From Expert Systems to Knowledge-based Modules 155
References 157
Chapter 7. INTRODUCTION TO FUZZY LOGIC AND FUZZY SETS 159
1. Introduction 159
2. Uncertain versus Unknown Knowledge 160
3. Boolean Logic and its quantification 161
4. Fuzzy Logic and Fuzzy Sets 162
5. Basic Fuzzy Set Theory 166
6. REFERENCES 176
Chapter 8. AN INTRODUCTION TO NEURAL NETWORKS 177
1 Overview 177
2 Neurophysiological Basis: Modelling Biological Hardware 178
3 Motivation 179
4 Contributions from Other Fields 180
5 Advantages 181
6 Biological Neural Networks 183
7 Artificial Neural Networks 189
8 Multilayer Feedforward Networks 196
9 Recurrent Networks 209
10 Concluding Remarks 212
Acknowledgements 212
References 213
PART II: CONTROL ENGINEERING 214
Road Map 216
Chapter 9. COMPUTER CONTROL SYSTEMS: AN INTRODUCTION 218
1. ORIGINS OF FEEDBACK CONTROL 218
2. TRENDS IN CONTROL 220
3. TOWARD DISTRIBUTED COMPUTER CONTROL SYSTEMS 223
4. DESIGN ISSUES OF DISTRIBUTED COMPUTER CONTROL SYSTEMS 228
5. NEW DIRECTIONS AND EMERGING TRENDS IN IMPLEMENTATION 233
REFERENCES 235
Chapter 10. Towards Intelligent control: Integration of AI in Control 236
1 Introduction to Intelligent control 236
2 The need for Intelligent Control 241
3 Intelligent Control Components 243
4 Control Engineering Applications of AI Techniques 249
5 Real-time issues 256
6 Comparison 259
7 Concluding remarks 260
References 260
PART III: REAL-TIME ISSUES 264
Road Map 266
Chapter 11. REAL-TIME AND COMMUNICATION ISSUES 268
1. INTRODUCTION 268
2. REQUIREMENTS FOR REAL-TIME AUTOMATION 269
3. REAL-TIME COMMUNICATIONS 270
4. COMMUNICATION SYSTEMS FOR DISTRIBUTED COMPUTER CONTROL 275
5. IMPLEMENTATION ISSUES 278
6. CONCLUSIONS 285
REFERENCES 286
Chapter 12. REAL TIME EXPERT SYSTEMS 287
1 REAL TIME SYSTEMS 287
2 EXPERT SYSTEMS 289
3 RTES Architectures 291
4 Temporal Representation and Reasoning 296
5 Guaranteed Response Time 302
6 Examples 303
References 309
PART IV: CAD Systems using Expert Systems 312
Road Map 314
Chapter 13. USER INTERFACE ISSUES AND THE ROLE OF ARTIFICIAL INTELLIGENCE in COMPUTER-AIDED CONTROL ENGINEERING 316
ABSTRACT 316
KEYWORDS 316
INTRODUCTION 316
A MODEL OF COMPUTER-AIDED DESIGN 317
THE DEVELOPMENT OF CACSD 320
THE STATE OF THE ART IN COMPUTER-AIDED CONTROL ENGINEERING 328
APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN CACE 332
THE FOURTH GENERATION OF CACE 343
CONCLUSIONS 347
REFERENCES 347
PART V: INTELLIGENT CONTROL 352
Road Map 354
Chapter 14. FUZZY CONTROLLERS 356
1 Intelligent control 356
2 Fuzzy Controller Structure 363
3 FC Analysis and Design 373
4 FC Supervision 378
5 REFERENCES 379
Chapter 15. Adaptive Fuzzy Control 381
Abstract 381
Keywords 381
1 Introduction 381
2 Fuzzy control 382
3 Self-organizing fuzzy control 385
4 Extension of fuzzy rules 389
5 Real-time fuzzy expert control environment 390
6 An adaptive fuzzy expert controller 393
7 Experiments and results 395
8 Discussion and conslusions 398
References 399
Chapter 16. NEURAL NETWORKS FOR CONTROL 401
1 Introduction 401
2 Representation of Dynamic Systems 402
3 System Identification 404
4 Neural Controllers 406
5 Adaptive Control using NN 409
6 Some Relevant Applications 412
Acknowledgements 413
7 References 413
Chapter 17. Associative Memories: The CMAC approach 416
Abstract 416
Keywords 416
1 Introduction 416
2 CMAC 417
3 Comparison with classic neural networks 426
4 Modelling and control using CMAC 427
5 Summary and concluding remarks 433
References 433
PART VI: SUPERVISORY CONTROL/MONITORING/OPTIMIZATION 436
Road Map 438
Chapter 18. SUPERVISED ADAPTIVE CONTROL 440
1 Introduction 440
2 Adaptive Control 442
3 Adaptive Control and Supervision 446
4 Indicators: a Tool for Supervision 451
5 Implementation of Supervision Functions 457
References 468
Chapter 19. MONITORING AND FAULT DIAGNOSIS IN CONTROL ENGINEERING 469
1 Introduction 469
2. Architecture of knowledge bases required for implementing Expert control systems 480
3 Requirements for a Real-Time Expert Monitoring System 487
4. Fault Diagnosis: A Generic Example of an Expert System 494
5. Applications to Control Systems 500
6. References 508
Chapter 20. Expert Governed Numerical Optimization 510
Abstract 510
Keywords 510
Introduction 510
Optimization 511
Constrained / Unconstrained Optimization 515
Function Minimisation Techniques 517
Problems with existing programs 519
Expert Governed Numerical Optimization 520
Implementation aspects 523
Example 526
Conclusions 529
References 530
Author Index 532
Subject Index 540

Produkt-Details

• Erscheint lt. Verlag: 22.10.2013
• Sprache: englisch
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Technik ► Bauwesen
• Themenwelt: Technik ► Maschinenbau
• ISBN-10: 0-08-091263-X / 008091263X
• ISBN-13: 978-0-08-091263-9 / 9780080912639