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

B. Visakamoorthi, K. Subramanian and P. Muthukumar

Applied Mathematics and Computation, 2022, vol. 435, issue C

Abstract: 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 constructed 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 system is stochastically stable and possesses the dissipativity performance. For this, a sufficient condition is derived for the proposed system in the form of linear matrix inequalities. 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.

Keywords: Fuzzy Markov jump system; Actuator fault; Dissipativity analysis; Non-fragile sampled-data control; Hidden Markov model (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:435:y:2022:i:c:s0096300322005288

DOI: 10.1016/j.amc.2022.127454

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