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

Qiang Li, Jinling Liang, Weiqiang Gong, Kai Wang and Jinling Wang

Mathematics and Computers in Simulation (MATCOM), 2024, vol. 218, issue C, 204-222

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.

Keywords: Complex-valued networks; State estimation; Semi-Markov process; Event-triggered scheme; General uncertain transition rates (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:218:y:2024:i:c:p:204-222

DOI: 10.1016/j.matcom.2023.11.028

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