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Nonfragile state estimation for semi-Markovian switching CVNs with general uncertain transition rates: An event-triggered scheme

Author

Listed:
  • Li, Qiang
  • Liang, Jinling
  • Gong, Weiqiang
  • Wang, Kai
  • Wang, Jinling

Abstract

This paper tackles the problem of nonfragile state estimation for semi-Markovian switching complex-valued networks with time-varying delay. The concerned transition rates of the semi-Markov process are uncertain, including both the completely unknown ones and the inaccurately known ones with known bounds. To reduce the communication burden, a particular event-triggered generator is constructed, which depends on the latest available measurement output and a predefined positive threshold. Combining the stochastic analysis method with the Lyapunov stability theory, some less conservative criteria are obtained to ascertain the global asymptotic stability of the estimation error system in the mean-square sense. In addition, by solving some matrix inequalities, the desired nonfragile estimator gains are explicitly designed. Finally, a numerical example with simulations is given to illustrate effectiveness of the established estimation scheme.

Suggested Citation

  • Li, Qiang & Liang, Jinling & Gong, Weiqiang & Wang, Kai & Wang, Jinling, 2024. "Nonfragile state estimation for semi-Markovian switching CVNs with general uncertain transition rates: An event-triggered scheme," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 218(C), pages 204-222.
    • Handle: RePEc:eee:matcom:v:218:y:2024:i:c:p:204-222
    DOI: 10.1016/j.matcom.2023.11.028
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    References listed on IDEAS

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    1. Iswarya, M. & Raja, R. & Cao, J. & Niezabitowski, M. & Alzabut, J. & Maharajan, C., 2022. "New results on exponential input-to-state stability analysis of memristor based complex-valued inertial neural networks with proportional and distributed delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 201(C), pages 440-461.
    2. Hui Li & Liping Yan & Yuqin Zhou & Yuanqing Xia & Xiaodi Shi, 2023. "Sequential fusion estimation for Markov jump systems with heavy-tailed noises," International Journal of Systems Science, Taylor & Francis Journals, vol. 54(9), pages 1910-1925, July.
    3. Jiancun Wu & Chen Peng & Hongchenyu Yang & Yu-Long Wang, 2022. "Recent advances in event-triggered security control of networked systems: a survey," International Journal of Systems Science, Taylor & Francis Journals, vol. 53(12), pages 2624-2643, September.
    4. Divya, H. & Sakthivel, R. & Karthick, S.A. & Aouiti, C., 2022. "Non-fragile control design for stochastic Markov jump system with multiple delays and cyber attacks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 192(C), pages 291-302.
    5. Li, Qiang & Liang, Jinling, 2022. "Non-fragile asynchronous state estimation for Markovian switching CVNs with partly accessible mode detection: The discrete-time case," Applied Mathematics and Computation, Elsevier, vol. 412(C).
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