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This book systematically studies the feedback control and filtering problems for nonlinear plants with limited communication channels based on T-S fuzzy models. By fully considering different network-induced phenomena, such as signal quantizations, time-delays, data packet dropouts, communication protocols, cyber attacks, and so on, some significant strategies are provided for various performance analysis and different controller/filter synthesis of fuzzy systems. The event-triggered mechanism is also mentioned to save the communication resource. Moreover, some results are extended to the fault detection and fault-tolerant control. The book provides some new methodologies in analysis and synthesis of fuzzy systems under communication channels, and can serve as a valuable reference material for researchers wishing to explore the area of control and filtering of fuzzy systems and networked systems.
This book discusses how to deal with such constraints to guarantee the system's design objectives, focusing on real-world dynamical systems such as Markovian jump systems, networked control systems, neural networks, and complex networks, which have recently excited considerable attention.
"Robust Output Feedback H-infinity Control and Filtering for Uncertain Linear Systems" discusses new and meaningful findings on robust output feedback H-infinity control and filtering for uncertain linear systems, presenting a number of useful and less conservative design results based on the linear matrix inequality (LMI) technique.
Starting with a T-S fuzzy system, the objective of this book is to design an H-infinity filter with gain variations that guarantee a prescribed H-infinity performance level. It also shows that the solution can be found by solving linear matrix inequalities.
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