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Further results on event-triggered H∞ networked control for neural networks with stochastic cyber-attacks

Author

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  • Feng, Zongying
  • Shao, Hanyong
  • Shao, Lin

Abstract

This paper is concerned with decentralized event-triggered H∞ networked control for neural networks (NNs) subject to two types of stochastic cyber-attacks. Firstly, a new dynamic event-triggered scheme is introduced to monitor the sampled data transmissions, and two independent Bernoulli distributed variables are used to describe the randomly occurring cyber-attacks. Secondly, based on the networked control, the closed-loop system is constructed under the stochastic cyber-attacks and limited network bandwidth. Thirdly, by the Lyapunov-Krasovskii functional (LKF) approach, an improved stability criterion is established to ensure the closed-loop system is mean-square asymptotical stability with a prescribed H∞ performance. Based on the criterion, desired control gain is determined. Finally, the effectiveness of the obtained result is illustrated by two numerical examples.

Suggested Citation

  • Feng, Zongying & Shao, Hanyong & Shao, Lin, 2020. "Further results on event-triggered H∞ networked control for neural networks with stochastic cyber-attacks," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    • Handle: RePEc:eee:apmaco:v:386:y:2020:i:c:s0096300320303921
    DOI: 10.1016/j.amc.2020.125431
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    References listed on IDEAS

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    1. Shao, Hanyong & Li, Huanhuan & Zhu, Chuanjie, 2017. "New stability results for delayed neural networks," Applied Mathematics and Computation, Elsevier, vol. 311(C), pages 324-334.
    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.
    3. Liu, Jinliang & Xia, Jilei & Tian, Engang & Fei, Shumin, 2018. "Hybrid-driven-based H∞ filter design for neural networks subject to deception attacks," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 158-174.
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    Cited by:

    1. Su, Qingyu & Wang, Handong & Sun, Chaowei & Li, Bo & Li, Jian, 2022. "Cyber-attacks against cyber-physical power systems security: State estimation, attacks reconstruction and defense strategy," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    2. Xie, Jiyang & Zhu, Shuqian & Zhang, Dawei, 2022. "A robust distributed secure interval observation approach for uncertain discrete-time positive systems under deception attacks," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    3. Li, Lei & Wang, Wenting & Ma, Qiang & Pan, Kunpeng & Liu, Xin & Lin, Lin & Li, Jian, 2021. "Cyber attack estimation and detection for cyber-physical power systems," Applied Mathematics and Computation, Elsevier, vol. 400(C).
    4. Ma, Yan & Zhang, Zhenzhen & Yang, Li & Chen, Hao & Zhang, Yihao, 2022. "A resilient optimized dynamic event-triggered mechanism on networked control system with switching behavior under mixed attacks," Applied Mathematics and Computation, Elsevier, vol. 430(C).

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