Fuzzy Modeling and Fuzzy Control

ISBN-13: 9780817644918 / Angielski / Twarda / 2006 / 416 str.

Huaguang Zhang; Derong Liu

Opis

Fuzzy logic methodology has proven effective in dealing with complex nonlinear systems containing uncertainties that are otherwise difficult to model. Technology based on this methodology is applicable to many real-world problems, especially in the area of consumer products. This book presents the first comprehensive, unified treatment of fuzzy modeling and fuzzy control, providing tools for the control of complex nonlinear systems. Coverage includes model complexity, model precision, and computing time. This is an excellent reference for electrical, computer, chemical, industrial, civil, manufacturing, mechanical and aeronautical engineers, and also useful for graduate courses in electrical engineering, computer engineering, and computer science.

Recenzje

From the reviews:

"Of the books on fuzzy control I have had a chance to study, this one ranks among the best. It can be recommended as a textbook for an advanced course in fuzzy control. Moreover, researchers as well as practitioners in the field of control will definitely profit from the book."
-SIAM Review

"After introducing some basic concepts and terminologies of fuzzy theory, the authors provide a systematic discussion about fundamental methodologies of fuzzy modeling and fuzzy control of complex nonlinear systems with uncertainty. This book is well written. All concepts and terminologies are carefully defined and explained. ... The book is aimed at graduate students and researchers in electrical engineering, computer engineering, computer science, physical sciences, and any of the engineering disciplines." (Peihua Qiu, Technometrics, Vol. 50 (3), August, 2008)

"This book presents a systematic framework targeting at fuzzy modeling and fuzzy control of nonlinear systems with uncertainties. ... [It] is a valuable resource for those researchers and practitioners interested in expanding their knowledge from fuzzy logic and application to nonlinear dynamical systems. It discusses a currently very active research topic and provides an excellent extension to a graduate course in nonlinear dynamic systems or fuzzy modeling and control. ... Professor Zhang and Professor Liu have made important research contributions in the area of fuzzy modeling and fuzzy control."
--IEEE Computational Intelligence Magazine

Spis treści

Preface Fuzzy Set Theory and Rough Set Theory Identification of the Takagi–Sugeno Fuzzy Model Fuzzy Model Identification Based on Rough Set Data Analysis Identification of the Fuzzy Hyperbolic Model Basic Methods for Fuzzy Inference and Control Fuzzy Inference and Control Methods Involving Two Kinds of Uncertainties Fuzzy Control Schemes via a Fuzzy Performance Evaluator Multivariable Predictive Control Based on the T–S Fuzzy Model Adaptive Control Methods Based on Fuzzy Basis Function Vectors Controller Design Based on the Fuzzy Hyperbolic Model Fuzzy H-infinity Filter Design for Nonlinear Discrete-Time Systems with Multiple Time-Delays Chaotification of the Fuzzy Hyperbolic Model Feedforward Fuzzy Control Approach Using the Fourier Integral Index

O autorze

Fuzzy logic methodology has been proven effective in dealing with complex nonlinear systems containing uncertainties that are otherwise difficult to model. Technology based on this methodology has been applied to many real-world problems, especially in the area of consumer products. This book presents the first unified and thorough treatment of fuzzy modeling and fuzzy control, providing necessary tools for the control of complex nonlinear systems. Careful consideration is given to questions concerning model complexity, model precision, and computing time.
In addition to being an excellent reference for electrical, computer, chemical, industrial, civil, manufacturing, mechanical and aeronautical engineers, the book may also be appropriate for classroom use in a graduate course in electrical engineering, computer engineering, and computer science. Applied mathematicians, control engineers, computer scientists, and physicists will benefit from the presentation as well.

Blurb

Fuzzy logic methodology has been proven effective in dealing with complex nonlinear systems containing uncertainties that are otherwise difficult to model. Technology based on this methodology has been applied to many real-world problems, especially in the area of consumer products. This book presents the first unified and thorough treatment of fuzzy modeling and fuzzy control, providing necessary tools for the control of complex nonlinear systems.

Based on three types of fuzzy models—the Mamdani fuzzy model, the Takagi–Sugeno fuzzy model, and the fuzzy hyperbolic model—the book addresses a number of important issues in fuzzy control systems, including fuzzy modeling, fuzzy inference, stability analysis, systematic design frameworks, robustness, and optimality. The authors develop several advanced control schemes, such as the fuzzy model-based generalized predictive control scheme, the fuzzy adaptive control scheme based on fuzzy basis function vectors, the fuzzy control scheme based on fuzzy performance evaluators, and the fuzzy sliding-mode control scheme. Careful consideration is given to questions concerning model complexity, model precision, and computing time.

In addition to being an excellent reference for electrical, computer, chemical, industrial, civil, manufacturing, mechanical and aeronautical engineers, the book may also be appropriate for classroom use in a graduate course in electrical engineering, computer engineering, and computer science. Applied mathematicians, control engineers, computer scientists, and physicists will benefit from the presentation as well.