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Analysis and Synthesis for Interval Type-2 Fuzzy-Model-Based Systems

Autor Hongyi Li, Ligang Wu, Hak-Keung Lam, Yabin Gao
en Limba Engleză Hardback – 9 mar 2016
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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Specificații

ISBN-13: 9789811005923
ISBN-10: 9811005923
Pagini: 257
Ilustrații: XIX, 257 p. 60 illus., 55 illus. in color.
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.57 kg
Ediția:1st ed. 2016
Editura: Springer Nature Singapore
Colecția Springer
Locul publicării:Singapore, Singapore

Cuprins

Introduction.- Stability and Stabilization of CTIT2FMBSs.- Output-feedback Control of CTIT2FMBSs.- Sampled-Data Control of CTIT2FMBSs.- Output Tracking Control of CTIT2FSs.- Switched Output-feedback Control of CTIT2FMBSs.- Filter Design of CTIT2FMBSs.- Fault Detection of CTIT2FMBSs.- Model Reduction of CTIT2FMBSs.- Optimal Control of DTIT2FMBSs.- State-feedback Control of DTIT2FMBSs.- Static Output-feedback Control of DTIT2FMBSs.- Guaranteed Cost Output Tracking Control of DTIT2FMBSs.

Recenzii

“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)

Notă biografică

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. 

Textul de pe ultima copertă

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.

Caracteristici

The first book on modeling, analysis and synthesis of interval type-2 TS fuzzy systems Develops a uniform accurate method which is capable of dealing with uncertainties existing in the membership functions Presents a systematic procedure of analysis and synthesis of the interval type-2 fuzzy systems with several system performance indexes Provides numerous simulation results for various examples, which fill certain gaps in this area of reach and may serve as benchmark solutions for the readers Extends the proposed method and corresponding formulations to static analysis Includes supplementary material: sn.pub/extras