A First Course in Fuzzy and Neural Control

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

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English

Chapman & Hall/CRC
12 November 2002

Fuzzy set theory; Automatic control engineering

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.

By: Hung T. Nguyen, Nadipuram R. Prasad, Carol L. Walker, Elbert A. Walker
Imprint: Chapman & Hall/CRC
Country of Publication: United States
Dimensions: Height: 234mm, Width: 156mm, Spine: 22mm
Weight: 632g
ISBN: 9781584882442
ISBN 10: 1584882441
Pages: 312
Publication Date: 12 November 2002
Audience: College/higher education , A / AS level
Format: Hardback
Publisher's Status: Active

A Prelude to Control Theory. Mathematical Models in Control. Fuzzy Logic for Control. Fuzzy Control. Neural Networks for Control. Neural Control. Fuzzy-Neural and Neural-Fuzzy Control. Applications.

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