H∞ synchronization of semi-Markovian jump neural networks with random sensor nonlinearities via adaptive event-triggered output feedback control

Xingxing Song, Hongqian Lu, Yao Xu and Wuneng Zhou

Mathematics and Computers in Simulation (MATCOM), 2022, vol. 198, issue C, 1-19

Abstract: In this paper, the H∞ synchronization problem of semi-Markovian jump neural networks (s-MJNNs) based on adaptive event-triggered scheme (AETS) output feedback control is studied. Also, the time-varying delay and leakage delay are considered in the system model. In order to solve the problems that the state of the system is not completely observable and limited network resources, an output feedback controller with AETS is designed. At the same time, in order to describe the performance of the sensor in the feedback link, the random nonlinear phenomenon of the sensor is described by the variable complying with Bernoulli probability distribution. A suitable Lyapunov–Krasovskii functional (LKF) is constructed and the bounds of integral terms are estimated by affine Bessel–Legendre inequality. Finally, sufficient conditions for asymptotic stability of the synchronization error system are obtained. And, two numerical examples show the feasibility of the research work.

Keywords: H∞ synchronization; Semi-Markovian jump neural network; Output feedback control; AETS; Sensor nonlinearities (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:198:y:2022:i:c:p:1-19

DOI: 10.1016/j.matcom.2022.02.008

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