Fuzzy Control and Modeling: Analytical Foundations and Applications

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9780780334977: Fuzzy Control and Modeling: Analytical Foundations and Applications

The emerging, powerful fuzzy control paradigm has led to the worldwide success of countless commercial products and real-world applications. Fuzzy control is exceptionally practical and cost-effective due to its unique ability to accomplish tasks without knowing the mathematical model of the system, even if it is nonlinear, time varying and complex. Nevertheless, compared with the conventional control technology, most fuzzy control applications are developed in an ad hoc manner with little analytical understanding and without rigorous system analysis and design.

Fuzzy Control and Modeling is the only book that establishes the analytical foundations for fuzzy control and modeling in relation to the conventional linear and nonlinear theories of control and systems. The coverage is up-to-date, comprehensive, in-depth and rigorous. Numeric examples and applications illustrate the utility of the theoretical development.

Important topics discussed include:

  • Structures of fuzzy controllers/models with respect to conventional fuzzy controllers/models
  • Analysis of fuzzy control and modeling in relation to their classical counterparts
  • Stability analysis of fuzzy systems and design of fuzzy control systems
  • Sufficient and necessary conditions on fuzzy systems as universal approximators
  • Real-time fuzzy control systems for treatment of life-critical problems in biomedicine
Fuzzy Control and Modeling is a self-contained, invaluable resource for professionals and students in diverse technical fields who aspire to analytically study fuzzy control and modeling.

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About the Author:

Hao Ying is an associate professor in the Department of Electrical and Computer Engineering at Wayne State University, after leaving the faculty of University of Texas Medical Branch in 2000. Dr. Ying began fuzzy control research in 1981. In 1987 he established the world's first analytical connection between a fuzzy controller and a conventional controller. In 1989 he developed the world's first clinical fuzzy control application-real-time control of blood pressure. He has been making systematic contributions to analytical issues fundamental to fuzzy control and systems.

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