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Finite-time reliable filtering for Takagi–Sugeno fuzzy semi-Markovian jump systems

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  • Sakthivel, R.
  • Suveetha, V.T.
  • Nithya, V.
  • Sakthivel, R.

Abstract

In this study, we concentrate on the problem of a finite-time reliable filter design for discrete-time Takagi–Sugeno fuzzy semi-Markovian jump systems with time-varying delay, sensor faults and randomly occurring uncertainties. To be precise, the time-varying transition probability matrices for the considered system are described by a semi-Markov process. Specifically, the objective is to design a reliable filter ensuring the strict dissipativity performance of the augmented filtering error system in the presence of sensor failures. Further, the stochastic variables describing the random nature of the parameter uncertainties are assumed to follow the Bernoulli distribution. A new finite-time stochastic stability criterion based on reciprocally convex approach and Lyapunov–Krasovskii stability theory is established in terms of linear matrix inequalities for the considered Takagi–Sugeno fuzzy semi-Markovian jump systems. Moreover, the delay-dependent conditions are established to guarantee the augmented filtering error system to be stochastically finite-time bounded and to achieve a prescribed strict dissipativity performance level for all admissible uncertainties and sensor faults. Finally, a numerical example is provided to show the correctness and effectiveness of the proposed method.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:matcom:v:185:y:2021:i:c:p:403-418
    DOI: 10.1016/j.matcom.2020.12.034
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    References listed on IDEAS

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    1. R. Samidurai & R. Sriraman & Song Zhu, 2019. "Stability and dissipativity analysis for uncertain Markovian jump systems with random delays via new approach," International Journal of Systems Science, Taylor & Francis Journals, vol. 50(8), pages 1609-1625, June.
    2. Samidurai, R. & Sriraman, R., 2019. "Robust dissipativity analysis for uncertain neural networks with additive time-varying delays and general activation functions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 201-216.
    3. Ge, Chao & Shi, Yanpen & Park, Ju H. & Hua, Changchun, 2019. "Robust H∞ stabilization for T-S fuzzy systems with time-varying delays and memory sampled-data control," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 500-512.
    4. M. Sathishkumar & R. Sakthivel & O. M. Kwon & B. Kaviarasan, 2017. "Finite-time mixed and passive filtering for Takagi–Sugeno fuzzy nonhomogeneous Markovian jump systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(7), pages 1416-1427, May.
    5. Kumar, S. Vimal & Anthoni, S. Marshal & Raja, R., 2019. "Dissipative analysis for aircraft flight control systems with randomly occurring uncertainties via non-fragile sampled-data control," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 217-226.
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    2. 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).

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