Intelligent Control

Aspects of Fuzzy Logic and Neural Nets

By: Christopher J. Harris, C. G. Moore, M. Brown

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Hardcover | 1 March 1993

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Hardcover
400 Pages

Dimensions(cm)
22.23 x 15.88 x 2.54

Hardcover

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With increasing demands for high precision autonomous control over wide operating envelopes, conventional control engineering approaches are unable to adequately deal with system complexity, nonlinearities, spatial and temporal parameter variations, and with uncertainty. Intelligent Control or self-organizing/learning control is a new emerging discipline that is designed to deal with problems. Rather than being model based, it is experiential based. Intelligent control is the amalgam of the disciplines of artificial intelligence, systems theory and operations research. It uses most recent experiences or evidence to improve its performance through a variety of learning schemes, that for practical implementation must demonstrate rapid learning convergence, be temporally stable, be robust to parameter changes and internal and external disturbances. It is shown in this book that a wide class of fuzzy logic and neural net based learning algorithms satisfy these conditions. It is demonstrated that this class of intelligent controllers is based upon a fixed nonlinear mapping of the input (sensor) vector, followed by an output layer linear mapping with coefficients that are updated by various first order learning laws. Under these conditions self-organizing fuzzy logic controllers and neural net controllers have common learning attributes. A theme example of the navigation and control of an autonomous guided vehicle is included throughout, together with a series of bench examples to demonstrate this new theory and its applicability.

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You Can Find This Book In

Non-Fiction Mathematics Mathematical Foundation Mathematical Logic Computing & I.T.Computer Science Artificial Intelligence Neural Networks & Fuzzy Systems Applied Mathematics Fuzzy Set Theory Engineering & Technology Electronics & Communications Engineering

Electronics Engineering Automatic Control Engineering Booktopia Publisher Services World Scientific Publishing

Preface
An Introduction to Intelligent Control	p. 1
Introductory Fuzzy Logic	p. 37
Fuzzy Logic Controller Structure and Design	p. 90
The Static Fuzzy Logic Controller	p. 135
Self-Organising Fuzzy Logic Control	p. 170
Indirect Self-Organising Fuzzy Logic Controllers	p. 215
Case Studies of Indirect Adaptive Fuzzy Control	p. 254
Neural Network Approximation Capability for Control and Modelling	p. 282
The B-Spline Neural Network and Fuzzy Logic	p. 314
The Appendix: Mathematical Prerequisites	p. 358
Subject Index	p. 373
Table of Contents provided by Blackwell. All Rights Reserved.

Intelligent Control

Aspects of Fuzzy Logic and Neural Nets

At a Glance

Hardcover

Shipping

How to return your order

Defective items

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