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A memory behavior related hybrid event-triggered mechanism for an improved robust control on neural networks

Author

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  • Liu, Yang
  • Zhang, Zhenzhen
  • Chen, Hao
  • Zhong, Shouming

Abstract

This paper addresses an H∞ control approach on neural networks with hybrid-triggered mechanism (HTM) under deception attacks. With the aim of mitigating the burden of the transmission network, an HTM is introduced to handle unforeseen non-ideal environment influence, which is characterized by Bernoulli distribution. The weight combination coefficients ϵj related to historical information are conducted to develop an improved HTM. By taking into account network-induced delay, and the randomly happened deception attacks in transmission network, a Lyapunov–Krasovskii functional (LKF) is constructed. Using linear matrix inequality (LMI), sufficient conditions are formed to render the system asymptotically stable and the H∞ hybrid-triggered controller is designed. Finally, simulation examples are executed to validate the feasibility of the developed method.

Suggested Citation

  • Liu, Yang & Zhang, Zhenzhen & Chen, Hao & Zhong, Shouming, 2023. "A memory behavior related hybrid event-triggered mechanism for an improved robust control on neural networks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 212(C), pages 1-20.
  • Handle: RePEc:eee:matcom:v:212:y:2023:i:c:p:1-20
    DOI: 10.1016/j.matcom.2023.04.023
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    References listed on IDEAS

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    1. Maharajan, C. & Raja, R. & Cao, Jinde & Rajchakit, G. & Alsaedi, Ahmed, 2018. "Novel results on passivity and exponential passivity for multiple discrete delayed neutral-type neural networks with leakage and distributed time-delays," Chaos, Solitons & Fractals, Elsevier, vol. 115(C), pages 268-282.
    2. Zhang, Ruimei & Zeng, Deqiang & Zhong, Shouming & Yu, Yongbin, 2017. "Event-triggered sampling control for stability and stabilization of memristive neural networks with communication delays," Applied Mathematics and Computation, Elsevier, vol. 310(C), pages 57-74.
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