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Reduced-order filtering for semi-Markovian jump systems against randomly occurring false data injection attacks

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  • Kaviarasan, Boomipalagan
  • Kwon, Oh-Min
  • Park, Myeong Jin
  • Sakthivel, Rathinasamy

Abstract

This paper describes a mode-dependent reduced-order filtering problem for semi-Markovian jump systems with time-varying delay and external disturbance, where the measurement output is vulnerable to randomly occurring false data injection attacks. To facilitate analysis, the attacks are described by a nonlinear function that meets Lipschitz continuity and the possible attack scenarios are represented by a stochastic parameter that follows the Bernoulli distribution. Based on the information from the considered system and reduced-order filter, an augmented filtering system is constructed. Then, a convex optimization problem is formulated by using Lyapunov-Krasovskii stability theory and stochastic analysis. The filter gain matrices are efficiently derived as a result, ensuring that the augmented filtering system is stochastically stable and strictly (Q,S,R)−γ-dissipative. Through numerical examples, the advantages and effectiveness of the developed theoretical findings are clearly demonstrated.

Suggested Citation

  • Kaviarasan, Boomipalagan & Kwon, Oh-Min & Park, Myeong Jin & Sakthivel, Rathinasamy, 2023. "Reduced-order filtering for semi-Markovian jump systems against randomly occurring false data injection attacks," Applied Mathematics and Computation, Elsevier, vol. 444(C).
    • Handle: RePEc:eee:apmaco:v:444:y:2023:i:c:s0096300323000012
    DOI: 10.1016/j.amc.2023.127832
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    References listed on IDEAS

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