Hidden Markov model based non-fragile sampled-data control design for mode-dependent fuzzy systems with actuator faults

This paper investigates the dissipativity-based asynchronous sampled-data control design for a class of Takagi-Sugeno fuzzy Markovian jump systems along with time delay, gain fluctuations, and actuator failures . To do this, the hidden Markov model is introduced to describe the phenomenon of asynchronization between the controller and the given fuzzy jump systems. Then, a novel mode-dependent Lyapunov-Krasovskii functional is con-structed to achieve the stability conditions and expand the maximum sampling period of fuzzy systems. The main purpose of this study is to design the asynchronous non-fragile reliable control with sampled-data information such that the mode-dependent fuzzy sys-tem is stochastically stable and possesses the dissipativity performance. For this, a suffi-cient condition is derived for the proposed system in the form of linear matrix inequal-ities. Meanwhile, the less conservative results and the desired controller are attained by solving the inequalities. At last, the validity and the superiority of our design technique are demonstrated by numerical examples.(c) 2022 Elsevier Inc. All rights reserved.

Automated summary

This paper investigates the dissipativity-based asynchronous sampled-data control design for a class of Takagi-Sugeno fuzzy Markovian jump systems along with time delay, gain fluctuations, and actuator failures. The hidden Markov model is introduced to describe the asynchronization phenomenon, and a novel mode-dependent Lyapunov-Krasovskii functional is constructed to achieve stability conditions and extend the maximum sampling period of fuzzy systems. The study aims to design asynchronous non-fragile reliable control with sampled-data information for stochastically stable and dissipative fuzzy systems. Sufficient conditions in the form of linear matrix inequalities are derived, and less conservative results and desired controllers are obtained by solving the inequalities. Numerical examples are provided to demonstrate the effectiveness and superiority of the proposed design technique.