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Dissipative filtering for singular Markovian jump systems with generally hybrid transition rates

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  • Tian, Yufeng
  • Wang, Zhanshan

Abstract

This paper studies the dissipative filtering of singular Markovian jump systems (SMJSs) with generally hybrid transition rates (GHTRs). The transition rates of the mode jumps are considered to be generally hybrid, which relax the traditional assumption in Markov jump systems that estimate errors must be completely symmetric. The introduced generally hybrid transition rates (GHTRs) make these systems more general and realistic. In order to deal with the GHTRs, a new approach named double-boundary approach is proposed. Then, a new integral inequality named Wirtinger-type free-matrix-based integral inequality (WFMII) is proposed to estimate Lyapunov-Krasovskii functional (LKF), in which some delay-product-type matrices are produced to fully link the relationship among time-varying delay and system states. Based on these ingredients, an explicit expression of the desired filter can be given to ensure the filtering error system to be stochastically admissible and strictly dissipative. The further examination to demonstrate the feasibility of the presented method is given by designing a filter of a two-loop circuit network.

Suggested Citation

  • Tian, Yufeng & Wang, Zhanshan, 2021. "Dissipative filtering for singular Markovian jump systems with generally hybrid transition rates," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    • Handle: RePEc:eee:apmaco:v:411:y:2021:i:c:s0096300321005816
    DOI: 10.1016/j.amc.2021.126492
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    References listed on IDEAS

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    1. Jin, Zhenghong & Wang, Zhanxiu, 2021. "Input-to-state stability of the nonlinear singular systems via small-gain theorem," Applied Mathematics and Computation, Elsevier, vol. 402(C).
    2. Li, Zhi-Min & Chang, Xiao-Heng & Yu, Lu, 2016. "Robust quantized H∞ filtering for discrete-time uncertain systems with packet dropouts," Applied Mathematics and Computation, Elsevier, vol. 275(C), pages 361-371.
    3. Sakthivel, R. & Suveetha, V.T. & Nithya, V. & Sakthivel, R., 2021. "Finite-time reliable filtering for Takagi–Sugeno fuzzy semi-Markovian jump systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 185(C), pages 403-418.
    4. Tan, Guoqiang & Wang, Zhanshan & Li, Cong, 2020. "H∞ performance state estimation of delayed static neural networks based on an improved proportional-integral estimator," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    5. Nithya, V. & Sakthivel, R. & Sakthivel, R. & Alzahrani, Faris, 2020. "Dissipative-based non-fragile filtering for fuzzy networked control systems with switching communication channels," Applied Mathematics and Computation, Elsevier, vol. 373(C).
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