Polynomial Fuzzy Model-Based Control Systems: Stability Analysis and Control Synthesis Using Membership Function Dependent Techniques (Studies in Systems, Decision and Control, Band 64) - Softcover

Über die Autorin bzw. den Autor

Hongyi Li received B.S. and M.S. degrees in mathematics from Bohai University, Jinzhou, China, in 2006 and 2009, respectively, and the Ph.D. degree in intelligent control from the University of Portsmouth, Portsmouth, UK, in 2012. He is currently a Professor of the College of Engineering, Bohai University. He was a Research Associate with the Department of Mechanical Engineering, University of Hong Kong and Hong Kong Polytechnic University, from June 2010 to September 2010 and from September 2012 to December 2012, respectively. His research interests include fuzzy control, robust control, and their applications. He is also an Associate Editor/Editorial Board member for several international journals, including Neurocomputing, Circuits, Systems, and Signal Processing, Shock and Vibration, etc. Ligang Wu, Professor, Space Control and Inertial Technology Research Center, Harbin Institute of Technology. Hak-Keung Lam, Professor, Department of Informatics, King's College London. Yabin Gao, Student, Space Control and Inertial Technology Research Center, Harbin Institute of Technology.

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This book presents recent research on the stability analysis of polynomial-fuzzy-model-based control systems where the concept of partially/imperfectly matched premises and membership-function dependent analysis are considered. The membership-function-dependent analysis offers a new research direction for fuzzy-model-based control systems by taking into account the characteristic and information of the membership functions in the stability analysis.

The book presents on a research level the most recent and advanced research results, promotes the research of polynomial-fuzzy-model-based control systems, and provides theoretical support and point a research direction to postgraduate students and fellow researchers. Each chapter provides numerical examples to verify the analysis results, demonstrate the effectiveness of the proposed polynomial fuzzy control schemes, and explain the design procedure. The book is comprehensively written enclosing detailed derivation steps and mathematical derivations also for readers without extensive knowledge on the topics including students with control background who are interested in polynomial fuzzy model-based control systems.