A First Course in Fuzzy and Neural Control: 1st Edition (Hardback) book cover

A First Course in Fuzzy and Neural Control

1st Edition

By Hung T. Nguyen, Nadipuram R. Prasad, Carol L. Walker, Elbert A. Walker

Chapman and Hall/CRC

312 pages | 156 B/W Illus.

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pub: 2002-11-12
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Description

Although the use of fuzzy control methods has grown nearly to the level of classical control, the true understanding of fuzzy control lags seriously behind. Moreover, most engineers are well versed in either traditional control or in fuzzy control-rarely both. Each has applications for which it is better suited, but without a good understanding of both, engineers cannot make a sound determination of which technique to use for a given situation.

A First Course in Fuzzy and Neural Control is designed to build the foundation needed to make those decisions. It begins with an introduction to standard control theory, then makes a smooth transition to complex problems that require innovative fuzzy, neural, and fuzzy-neural techniques. For each method, the authors clearly answer the questions: What is this new control method? Why is it needed? How is it implemented? Real-world examples, exercises, and ideas for student projects reinforce the concepts presented.

Developed from lecture notes for a highly successful course titled The Fundamentals of Soft Computing, the text is written in the same reader-friendly style as the authors' popular A First Course in Fuzzy Logic text. A First Course in Fuzzy and Neural Control requires only a basic background in mathematics and engineering and does not overwhelm students with unnecessary material but serves to motivate them toward more advanced studies.

Reviews

"…Simple, concise, and easy to read from the student's perspective…a welcome addition to the…references in the fields of neural and fuzzy systems."

SIAM Review Vol. 46, No. 1

Table of Contents

A PRELUDE TO CONTROL THEORY

An Ancient Control System

Examples of Control Problems

Open-Loop Control Systems

Closed-Loop Control Systems

Stable and Unstable Systems

A Look at Controller Design

Exercises and Projects

MATHEMATICAL MODELS IN CONTROL

Introductory Examples: Pendulum Problems

State Variables and Linear Systems

Controllability and Observability

Stability

Controller Design

State Variable Feedback Control

Second-Order Systems

Higher-Order Systems

Proportional-Integral-Derivative Control

Nonlinear Control Systems

Linearization

Exercises and Projects

FUZZY LOGIC FOR CONTROL

Fuzziness and Linguistic Rules

Fuzzy Sets in Control

Combining Fuzzy Sets

Sensitivity of Functions

Combining Fuzzy Rules

Truth Tables for Fuzzy Logic

Fuzzy Partitions

Fuzzy Relations

Defuzzification

Level Curves and Alpha-Cuts

Universal Approximation

Exercises and Projects

FUZZY CONTROL

A Fuzzy Controller for an Inverted Pendulum

Main Approaches to Fuzzy Control

Stability of Fuzzy Control Systems

Fuzzy Controller Design

Exercises and Projects

NEURAL NETWORKS FOR CONTROL

What is a Neural Network? .

Implementing Neural Networks

Learning Capability

The Delta Rule

The Back Propagation Algorithm

Example: Training a Neural Network

Practical Issues in Training

Exercises and Projects

NEURAL CONTROL

Why Neural Networks in Control

Inverse Dynamics

Neural Networks in Direct Neural Control

Example: Temperature Control

Neural Networks in Indirect Neural Control

Exercises and Projects

FUZZY-NEURAL AND NEURAL-FUZZY CONTROL

Fuzzy Concepts in Neural Networks

Basic Principles of Fuzzy-Neural Systems

Basic Principles of Neural-Fuzzy Systems

Generating Fuzzy Rules and Membership Functions

Exercises and Projects

APPLICATIONS

A Survey of Industrial Applications

Cooling Scheme for Laser Materials

Color Quality Processing

Identification of Trash in Cotton

Integrated Pest Management Systems

Comments

Bibliography

Index

Subject Categories

BISAC Subject Codes/Headings:
MAT003000
MATHEMATICS / Applied