Fuzzy Controller Design: Theory and Applications / Edition 1

by Zdenko Kovacic, Stjepan Bogdan

Overview

Fuzzy control methods are critical for meeting the demands of complex nonlinear systems. They bestow robust, adaptive, and self-correcting character to complex systems that demand high stability and functionality beyond the capabilities of traditional methods. A thorough treatise on the theory of fuzzy logic control is out of place on the design bench. That is why Fuzzy Controller Design: Theory and Applications offers laboratory- and industry-tested algorithms, techniques, and formulations of real-world problems for immediate implementation.

With surgical precision, the authors carefully select the fundamental elements of fuzzy logic control theory necessary to formulate effective and efficient designs. The book supplies a springboard of knowledge, punctuated with examples worked out in MATLAB®/SIMULINK®, from which newcomers to the field can dive directly into applications. It systematically covers the design of hybrid, adaptive, and self-learning fuzzy control structures along with strategies for fuzzy controller design suitable for on-line and off-line operation. Examples occupy an entire chapter, with a section devoted to the simulation of an electro-hydraulic servo system. The final chapter explores industrial applications with emphasis on techniques for fuzzy controller implementation and different implementation platforms for various applications.

With proven methods based on more than a decade of experience, Fuzzy Controller Design: Theory and Applications is a concise guide to the methodology, design steps, and formulations for effective control solutions.

Product Details

ISBN-13:	9780849337475
Publisher:	Taylor & Francis
Publication date:	12/12/2005
Series:	Automation and Control Engineering , #19
Pages:	416
Product dimensions:	6.00(w) x 9.00(h) x (d)

About the Author

Zdenko Kovacic, Stjepan Bogdan

Table of Contents

Introduction. Fuzzy Controller Design. Initial Setting of Fuzzy Controllers. Complex Fuzzy Controller Structures. Self-Organizing Fuzzy Controller. Fuzzy Controllers as MATLAB Superblocks. Implementation of Fuzzy Controllers for Industrial Applications.