Fuzzy Modeling And Fuzzy Control


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Bibliographic Information

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Fuzzy Modeling and Fuzzy Control. Description 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.

Fuzzy control - Scholarpedia

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.

Product details Format Hardback pages Dimensions x x Illustrations note 50 Tables, black and white; XVI, p. Other books in this series. Linear Systems Theory Ben M. Add to basket. Robot Manipulator Control Frank L. Back cover copy 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.

Insight Into Fuzzy Modeling

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. Review Text 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.

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. Keqin Gu.

About this book

Ashish Tewari. Sasa V. Harry G. Guillermo J. El-Kebir Boukas. Pedro Balaguer. Hebertt Sira-Ramirez.


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Marcio S. De Queiroz. Frank L. Sunil Kumar Agrawal. Warren E. Sunil Kumar Pullarcot. Yuanlong Li. Home Contact us Help Free delivery worldwide. Free delivery worldwide. Bestselling Series. Harry Potter. Popular Features.

1. Fuzzy connectives based on t-norms

New Releases. Fuzzy Modeling and Fuzzy Control. Description Fuzzy logic methodology has proven effective in dealing with complex nonlinear systems containing uncertainties that are otherwise difficult to model.

Fuzzy 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.