IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v386y2020ics0096300320303921.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300320303921
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2020.125431?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Yan & Mei, Jingling & Li, Wenxue, 2018. "Stochastic stabilization problem of complex networks without strong connectedness," Applied Mathematics and Computation, Elsevier, vol. 332(C), pages 304-315.
    2. 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).
    3. Huang, Xin & Dong, Jiuxiang, 2020. "A Robust Dynamic Compensation Approach for Cyber-Physical Systems Against Multiple Types of Actuator Attacks," Applied Mathematics and Computation, Elsevier, vol. 380(C).
    4. Tu, Zhengwen & Zhao, Yongxiang & Ding, Nan & Feng, Yuming & Zhang, Wei, 2019. "Stability analysis of quaternion-valued neural networks with both discrete and distributed delays," Applied Mathematics and Computation, Elsevier, vol. 343(C), pages 342-353.
    5. Hong, Yaxian & Bin, Honghua & Huang, Zhenkun, 2019. "Synchronization of state-switching hopfield-type neural networks: A quantized level set approach," Chaos, Solitons & Fractals, Elsevier, vol. 129(C), pages 16-24.
    6. Liu, Yunfeng & Song, Zhiqiang & Tan, Manchun, 2019. "Multiple μ-stability and multiperiodicity of delayed memristor-based fuzzy cellular neural networks with nonmonotonic activation functions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 159(C), pages 1-17.
    7. Wang, Lingyu & Huang, Tingwen & Xiao, Qiang, 2018. "Global exponential synchronization of nonautonomous recurrent neural networks with time delays on time scales," Applied Mathematics and Computation, Elsevier, vol. 328(C), pages 263-275.
    8. Yao, Xueqi & Zhong, Shouming & Hu, Taotao & Cheng, Hong & Zhang, Dian, 2019. "Uniformly stable and attractive of fractional-order memristor-based neural networks with multiple delays," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 392-403.
    9. 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.
    10. Wu, Xifen & Bao, Haibo, 2023. "H∞ state estimation for multiplex networks with randomly occurring sensor saturations," Applied Mathematics and Computation, Elsevier, vol. 437(C).
    11. Yan, Lisha & Wang, Zhen & Zhang, Mingguang & Fan, Yingjie, 2023. "Sampled-data control for mean-square exponential stabilization of memristive neural networks under deception attacks," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    12. Zeng, Deqiang & Zhang, Ruimei & Liu, Yajuan & Zhong, Shouming, 2017. "Sampled-data synchronization of chaotic Lur’e systems via input-delay-dependent-free-matrix zero equality approach," Applied Mathematics and Computation, Elsevier, vol. 315(C), pages 34-46.
    13. Li, Xin & Wei, Guoliang & Ding, Derui, 2021. "Distributed resilient interval estimation for sensor networks under aperiodic denial-of-service attacks and adaptive event-triggered protocols," Applied Mathematics and Computation, Elsevier, vol. 409(C).
    14. Zeng, Deqiang & Pu, Zhilin & Zhang, Ruimei & Zhong, Shouming & Liu, Yajuan & Wu, Guo-Cheng, 2019. "Stochastic reliable synchronization for coupled Markovian reaction–diffusion neural networks with actuator failures and generalized switching policies," Applied Mathematics and Computation, Elsevier, vol. 357(C), pages 88-106.
    15. Gao, Zifan & Zhang, Dawei & Zhu, Shuqian, 2023. "Hybrid event-triggered synchronization control of delayed chaotic neural networks against communication delay and random data loss," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    16. Zeng, Pengyu & Deng, Feiqi & Gao, Xiaobin & Liu, Xiaohua, 2021. "Sampled-data resilient H∞ control for networked stochastic systems subject to multiple attacks," Applied Mathematics and Computation, Elsevier, vol. 405(C).
    17. Arunagirinathan, S. & Lee, T.H., 2024. "Generalized delay-dependent reciprocally convex inequality on stability for neural networks with time-varying delay," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 217(C), pages 109-120.
    18. Shu, Jinlong & Wu, Baowei & Xiong, Lianglin, 2022. "Stochastic stability criteria and event-triggered control of delayed Markovian jump quaternion-valued neural networks," Applied Mathematics and Computation, Elsevier, vol. 420(C).
    19. Zhu, Sha & Bao, Haibo, 2022. "Event-triggered synchronization of coupled memristive neural networks," Applied Mathematics and Computation, Elsevier, vol. 415(C).
    20. Ge, Chao & Shi, Yanpen & Park, Ju H. & Hua, Changchun, 2019. "Robust H∞ stabilization for T-S fuzzy systems with time-varying delays and memory sampled-data control," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 500-512.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:386:y:2020:i:c:s0096300320303921. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.