Ebook: Methods and Applications of Intelligent Control

This book is concerned with Intelligent Control methods and applications. The field of intelligent control has been expanded very much during the recent years and a solid body of theoretical and practical results are now available. These results have been obtained through the synergetic fusion of concepts and techniques from a variety of fields such as automatic control, systems science, computer science, neurophysiology and operational research. Intelligent control systems have to perform anthropomorphic tasks fully autonomously or interactively with the human under known or unknown and uncertain environmental conditions. Therefore the basic components of any intelligent control system include cognition, perception, learning, sensing, planning, numeric and symbolic processing, fault detection/repair, reaction, and control action. These components must be linked in a systematic, synergetic and efficient way. Predecessors of intelligent control are adaptive control, self-organizing control, and learning control which are well documented in the literature. Typical application examples of intelligent controls are intelligent robotic systems, intelligent manufacturing systems, intelligent medical systems, and intelligent space teleoperators. Intelligent controllers must employ both quantitative and qualitative information and must be able to cope with severe temporal and spatial variations, in addition to the fundamental task of achieving the desired transient and steady-state performance. Of course the level of intelligence required in each particular application is a matter of discussion between the designers and users. The current literature on intelligent control is increasing, but the information is still available in a sparse and disorganized way.

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Content:
Front Matter....Pages i-xix
Front Matter....Pages 1-1
Introduction: Overview of Intelligent Controls....Pages 3-23
Fuzzy and Neural Intelligent Control: Basic Principles and Architectures....Pages 25-67
Intelligent Control Using Artificial Neural Networks and Fuzzy Logic: Recent Trends and Industrial Applications....Pages 69-102
Control of Robotic Manipulators Using Neural Networks — A Survey....Pages 103-136
Front Matter....Pages 137-137
Intelligent Process Control with Supervisory Knowledge-Based Systems....Pages 139-171
Fuzzy Model Based Predictive Controller....Pages 173-196
Fuzzy Adaptive Control Versus Model Reference Adaptive Control of Mutable Processes....Pages 197-216
Intelligent Control and Supervision Based on Fuzzy Petri Nets....Pages 217-243
Off Line Verification of an Intelligent Control....Pages 245-282
Intelligent Neurofuzzy Estimators and Multisensor Data Fusion....Pages 283-303
Linguistic Communication Channels....Pages 305-326
Front Matter....Pages 327-327
Intelligent Human — Machine Systems....Pages 329-356
Intelligent Control for a Robotic Acrobat....Pages 357-399
Adaptive and Learning Control of Robotic Manipulators....Pages 401-422
Fuzzy Evolutionary Algorithms and Automatic Robot Trajectory Generation....Pages 423-449
Application of Intelligent Control Techniques in Advanced AGC....Pages 451-484
Manufacturing Controller Design and Deadlock Avoidance Using a Matrix Model for Discrete Event Systems....Pages 485-508
Adaptive, Model Based Predictive, and Neural Control of the Welding Process....Pages 509-548
Back Matter....Pages 549-564

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Content:
Front Matter....Pages i-xix
Front Matter....Pages 1-1
Introduction: Overview of Intelligent Controls....Pages 3-23
Fuzzy and Neural Intelligent Control: Basic Principles and Architectures....Pages 25-67
Intelligent Control Using Artificial Neural Networks and Fuzzy Logic: Recent Trends and Industrial Applications....Pages 69-102
Control of Robotic Manipulators Using Neural Networks — A Survey....Pages 103-136
Front Matter....Pages 137-137
Intelligent Process Control with Supervisory Knowledge-Based Systems....Pages 139-171
Fuzzy Model Based Predictive Controller....Pages 173-196
Fuzzy Adaptive Control Versus Model Reference Adaptive Control of Mutable Processes....Pages 197-216
Intelligent Control and Supervision Based on Fuzzy Petri Nets....Pages 217-243
Off Line Verification of an Intelligent Control....Pages 245-282
Intelligent Neurofuzzy Estimators and Multisensor Data Fusion....Pages 283-303
Linguistic Communication Channels....Pages 305-326
Front Matter....Pages 327-327
Intelligent Human — Machine Systems....Pages 329-356
Intelligent Control for a Robotic Acrobat....Pages 357-399
Adaptive and Learning Control of Robotic Manipulators....Pages 401-422
Fuzzy Evolutionary Algorithms and Automatic Robot Trajectory Generation....Pages 423-449
Application of Intelligent Control Techniques in Advanced AGC....Pages 451-484
Manufacturing Controller Design and Deadlock Avoidance Using a Matrix Model for Discrete Event Systems....Pages 485-508
Adaptive, Model Based Predictive, and Neural Control of the Welding Process....Pages 509-548
Back Matter....Pages 549-564
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