Overview

This book develops a set of reference methods capable of modeling uncertainties existing in membership functions, and analyzing and synthesizing the interval type-2 fuzzy systems with desired performances. It also provides numerous simulation results for various examples, which fill certain gaps in this area of research and may serve as benchmark solutions for the readers.  Interval type-2 T-S fuzzy models provide a convenient and flexible method for analysis and synthesis of complex nonlinear systems with uncertainties.

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9789811092046

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Reviews

In this book the authors present analysis and control methods for interval type - 2 (IT2) Takagi-Sugeno (TS) fuzzy systems. ... Throughout the book, the theoretical results are illustrated by numerical examples. ... It may serve as a useful textbook for researchers and graduate students working in the field of type-2 TS systems based control. (Zsofia Lendek, Mathematical Reviews, April, 2017) This research monograph covers an important and timely topic of control of fuzzy model-based systems ... . In summary, the book is a valuable addition to the collection of readings on fuzzy control engineering. (Witold Pedrycz, zbMATH 1353.93003, 2017)

“In this book the authors present analysis and control methods for interval type – 2 (IT2) Takagi-Sugeno (TS) fuzzy systems. … Throughout the book, the theoretical results are illustrated by numerical examples. … It may serve as a useful textbook for researchers and graduate students working in the field of type-2 TS systems based control.” (Zsófia Lendek, Mathematical Reviews, April, 2017) “This research monograph covers an important and timely topic of control of fuzzy model-based systems … . In summary, the book is a valuable addition to the collection of readings on fuzzy control engineering.” (Witold Pedrycz, zbMATH 1353.93003, 2017)

This research monograph covers an important and timely topic of control of fuzzy model-based systems ... . In summary, the book is a valuable addition to the collection of readings on fuzzy control engineering. (Witold Pedrycz, zbMATH 1353.93003, 2017)

Author Information

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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