This book proposes analysis and design techniques for fuzzy systems using adaptive technology, event triggering mechanism, sampling control technology, and sliding mode control technology. The book covers stochastic stability, finite-time boundedness, actuator failure problems, fault-tolerant control, asynchronous control, and adaptive sliding mode control for uncertain fuzzy systems. The topic of fault-tolerant control will be of particular interest to readers because: (i) the internal hardware components of the system may age and fail to a greater or lesser extent; (ii) the external environment may suddenly change. With illustrations and tables, readers can easily follow the didactic approach and apply the methods to their own research. This book will be of particular interest to researchers and graduate students in control engineering and applied mathematics who are interested in the latest developments in fuzzy systems.
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This book proposes analysis and design techniques for fuzzy systems using adaptive technology, event triggering mechanism, sampling control technology, and sliding mode control technology.
Introduction.- Sampled Data Control for Uncertain Fuzzy Systems under Markovian Jump and FBM.- Observer Based Adaptive Sliding Mode Control for Markovian Jumping Fuzzy Systems.- Event Triggered Based Asynchronous Adaptive SMC Control for Fuzzy Systems.- Finite time boundedness of neutral semi Markovian jumping IT2 fuzzy neural networks.- Adaptive Event Triggered SMC Control for Fuzzy Systems with Actuator Failures.
Les mer
This book proposes analysis and design techniques for fuzzy systems using adaptive technology, event triggering mechanism, sampling control technology, and sliding mode control technology. The book covers stochastic stability, finite-time boundedness, actuator failure problems, fault-tolerant control, asynchronous control, and adaptive sliding mode control for uncertain fuzzy systems. The topic of fault-tolerant control will be of particular interest to readers because: (i) the internal hardware components of the system may age and fail to a greater or lesser extent; (ii) the external environment may suddenly change. With illustrations and tables, readers can easily follow the didactic approach and apply the methods to their own research. This book will be of particular interest to researchers and graduate students in control engineering and applied mathematics who are interested in the latest developments in fuzzy systems.
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Provides a systematic treatment of sliding mode control for fuzzy systems Uses a dynamic logarithmic quantizer to quantify the signals from sensor to controller and from controller to actuator Design a new event triggering rule based on quantified state
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Produktdetaljer

ISBN
9789819764990
Publisert
2025-02-06
Utgiver
Vendor
Springer Nature
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet

Om bidragsyterne

Changhong Wang received B.E., M. E., and Ph. D. degrees from Harbin Institute of Technology, Harbin, China in 1983, 1986 and 1991, respectively. He is presently a full professor and the deputy dean of Academy of Science and Technology, Harbin Institute of Technology. His research interests include intelligent control and intelligent system, inertial technology, robotics, and precision servo system.Email: cwang@hit.edu.cn

Xiao Xu received the M.Sc. degree in Applied Mathematics from Shanghai Normal University, Shanghai, China, in 2018. She is currently working toward the Ph.D. degree in Mathematics from Harbin Institute of Technology (Weihai). Her current research interests include fault-tolerant mechanism, event-triggered mechanism, sliding mode control, adaptive control.

Yonggui Kao received the B.E. degree from Beijing Jiaotong University in 1996. He received M.E. and Ph.D. degrees from Ocean University of China in 2005 and 2008, respectively. He now is a Professor at Department of Mathematics, Harbin Institute of Technology(Weihai). His research interest covers stochastic systems, impulsive systems, neural networks, stability theory and sliding mode control.

Hongwei Xia received B.E., M.E., and Ph.D. degrees from Harbin Institute of Technology, Harbin, China in 2002, 2004 and 2008, respectively. He is presently a full professor, Harbin Institute of Technology. His research interests include robust control, intelligent control and intelligent system.