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  3. Course In Fuzzy Systems and Control, A

Course In Fuzzy Systems and Control, A, 1st edition

  • LiXin Wang

Published by Prentice Hall (August 20th 1996) - Copyright © 1997

1st edition

Course In Fuzzy Systems and Control, A

ISBN-13: 9780135408827

Includes: Paperback
Free delivery
$101.00

What's included

  • Paperback

    You'll get a bound printed text.

Overview

Provides a comprehensive, self-tutorial course in fuzzy logic and its increasing role in control theory.KEY TOPICS:The book answers key questions about fuzzy systems and fuzzy control. It introduces basic concepts such as fuzzy sets, fuzzy union, fuzzy intersection and fuzzy complement. Learn about fuzzy relations, approximate reasoning, fuzzy rule bases, fuzzy inference engines, and several methods for designing fuzzy systems.MARKET:For professional engineers and students applying the principles of fuzzy logic to work or study in control theory.

Table of contents



1. Introduction.

Why Fuzzy Systems? What Are Fuzzy Systems? Where Are Fuzzy Systems Used and How? What Are the Major Research Fields in Fuzzy Theory? A Brief History of Fuzzy Theory and Applications. Summary and Further Readings. Exercises.

I. THE MATHEMATICS OF FUZZY SYSTEMS AND CONTROL.

2. Fuzzy Sets and Basic Operations on Fuzzy Sets.

From Classical Sets to Fuzzy Sets. Basic Concepts Associated with A Fuzzy Set. Operations on Fuzzy Sets. Summary and Further Readings. Exercises.
3. Further Operations on Fuzzy Sets.

Fuzzy Complement. Fuzzy Union —- The S-Norms. Fuzzy Intersection —- The T-Norms. Averaging Operators. Summary and Further Readings. Exercises.
4. Fuzzy Relations and the Extension Principle.

From Classical Relations to Fuzzy Relations. Compositions of Fuzzy Relations. The Extension Principle. Summary and Further Readings. Exercises.
5. Linguistic Variables and Fuzzy IF-THEN Rules.

From Numerical Variables to Linguistic Variables. Linguistic Hedges. Fuzzy IF-THEN Rules. Summary and Further Readings. Exercises.
6. Fuzzy Logic and Approximate Reasoning.

From Classical Logic to Fuzzy Logic. The Compositional Rule of Inference. Properties of the Implication Rules. Summary and Further Readings. Exercises.

II. FUZZY SYSTEMS AND THEIR PROPERTIES.

7. Fuzzy Rule Base and Fuzzy Inference Engine.

Fuzzy Rule Base. Fuzzy Inference Engine. Summary and Further Readings. Exercises.
8. Fuzzifiers and Defuzzifiers.

Fuzzifiers. Defuzzifiers. Summary and Further Readings. Exercises.
9. Fuzzy Systems as Nonlinear Mappings.

The Formulas of Some Classes of Fuzzy Systems. Fuzzy Systems As Universal Approximators. Summary and Further Readings. Exercises.
10. Approximation Properties of Fuzzy Systems I.

Preliminary Concepts. Design of A Fuzzy System. Approximation Accuracy of the Fuzzy System. Summary and Further Readings. Exercises.
11. Approximation Properties of Fuzzy Systems II.

Fuzzy Systems with Second-Order Approximation Accuracy. Approximation Accuracy of Fuzzy Systems with Maximum Defuzzifier. Summary and Further Readings. Exercises.

III. DESIGN OF FUZZY SYSTEMS FROM INPUT-OUTPUT DATA.

12. Design of Fuzzy Systems Using A Table Look-Up Scheme.

A Table Look-Up Scheme for Designing Fuzzy Systems from Input- Output Pairs. Application to Truck Backer-Upper Control. Application to Time-Series Prediction. Summary and Further Readings. Exercises and Projects.
13. Design of Fuzzy Systems Using Gradient Descent Training.

Choosing the Structure of Fuzzy Systems. Designing the Parameters by Gradient Descent. Application to Nonlinear Dynamic System Identifi

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