Intelligent Control: Principles, Techniques and ApplicationsThis book introduces the development process, structural theories and research areas of intelligent control; explains the knowledge representations, searching and reasoning mechanisms as the fundamental techniques of intelligent control; studies the theoretical principles and architectures of various intelligent control systems; analyzes the paradigms of representative applications of intelligent control; and discusses the research and development trends of the intelligent control.From the general point of view, this book possesses the following features: updated research results both in theory and application that reflect the latest advances in intelligent control; closed connection between theory and practice that enables readers to use the principles to their case studies and practical projects; and comprehensive materials that helps readers in understanding and learning. |
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Learning, Intell. Control
Contents
Preface vii | 1 |
References | 29 |
Methodology of Knowledge Representation | 35 |
References | 62 |
Hierarchical Control Systems | 87 |
References | 135 |
References | 180 |
Neurocontrol Systems | 242 |
References | 296 |
Learning Control Systems | 302 |
References | 347 |
Intelligent Control Systems in Application | 353 |
427 | |
Biography | 441 |
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Common terms and phrases
according actions activities adaptive algorithm application approach architecture artificial associated automatic called command complex components connected considered consists control system coordination corresponding cost decision defined Definition described desired discussed dynamic effective engineering error example execution exists expert control system expert system fault Figure function fuzzy controller fuzzy sets given goal graph hierarchical human IEEE implemented inference initial input integration intelligent control knowledge base layer learning control linguistic logic machine mapping measurement memory method module neural network neuron node object operation optimal organization output parameters path pattern performance planning plant problem procedure proposed real-time reasoning reference represent representation robot rules selected shown in Figure signal simulation solution solved space step structure symbol Table task techniques theory types variables vector
References to this book
Multisensor Fusion: A Minimal Representation Framework Rajive Joshi,Arthur C. Sanderson Limited preview - 1999 |