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Research Article | Open Access

Robust memory control design for semi-Markovian jump systems with cyber attacks

Ramalingam Sakthivel1Palanisamy Selvaraj1Oh-Min Kwon1( )Seong-Gon Choi2( )Rathinasamy Sakthivel3,4
School of Electrical Engineering, Chungbuk National University, Cheongju 28644, South Korea
School of Information and Communication Engineering, Chungbuk National University, Cheongju 28644, South Korea
Department of Applied Mathematics, Bharathiar University, Coimbatore 641046, India
Department of Mathematics, Sungkyunkwan University, Suwon 440746, South Korea
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Abstract

This paper addressed the problem of observer-based memory state feedback control design for semi-Markovian jump systems subject to input delays and external disturbances, where the measurement output was vulnerable to randomly occurring cyber attacks. To facilitate analysis, the cyber attacks were described by a nonlinear function that meets Lipschitz continuity and the possible attack scenarios were represented by a stochastic parameter that follows the Bernoulli distribution. Based on the information from the considered system and state observer, an augmented closed loop system was constructed. Then, by using the Lyapunov stability theory, an extended Wirtinger's integral inequality and stochastic analysis, the required stability criterion was proposed in the form of linear matrix inequalities. As a result, the control and observer gain matrices were efficiently derived, ensuring the stochastic stability of closed-loop systems with H performance, regardless of cyber attacks. To demonstrate the effectiveness and theoretical value of the proposed robust memory state feedback control design, simulation results were presented.

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Electronic Research Archive
Pages 7496-7510

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Cite this article:
Sakthivel R, Selvaraj P, Kwon O-M, et al. Robust memory control design for semi-Markovian jump systems with cyber attacks. Electronic Research Archive, 2023, 31(12): 7496-7510. https://doi.org/10.3934/era.2023378

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Received: 08 September 2023
Revised: 02 November 2023
Accepted: 16 November 2023
Published: 15 December 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)