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Dynamic event-triggered synchronization of complex networks with switching topologies: Asynchronous observer-based case

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  • Wu, Zhenyu
  • Chen, Jiawei
  • Zhang, Xuexi
  • Xiao, Zehui
  • Tao, Jie
  • Wang, Xiaofeng

Abstract

In this paper, the issue of observer-based synchronization for discrete complex networks with Markov switching topologies is investigated. First, the asynchronous phenomenon between the observer and the node is considered. By resorting to a hidden Markov model (HMM), an non-homogenous observer with an asynchronous topological structure and gain is developed to estimate the state of nodes. Second, for saving precious communication resources, the remote controller updates the control signal based on a dynamic event-triggered scheme (DETS). In this scheme, the threshold of DETS is improved into a diagonal threshold matrix, and the desired system performance can be obtained by flexibly arranging each entry of threshold matrix. To unify the works of the synchronization and state observation, an augmented error system (AES) is established. Subsequently, sufficient conditions for H∞ synchronization of complex networks with asynchronous constraints are proposed by choosing a suitable Lyapunov function. Finally, two simulation examples are implemented to demonstrate the effectiveness of the above results.

Suggested Citation

  • Wu, Zhenyu & Chen, Jiawei & Zhang, Xuexi & Xiao, Zehui & Tao, Jie & Wang, Xiaofeng, 2022. "Dynamic event-triggered synchronization of complex networks with switching topologies: Asynchronous observer-based case," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    • Handle: RePEc:eee:apmaco:v:435:y:2022:i:c:s0096300322004878
    DOI: 10.1016/j.amc.2022.127413
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    References listed on IDEAS

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    1. Liu, Chuang & Zhou, Nan & Zhan, Xiu-Xiu & Sun, Gui-Quan & Zhang, Zi-Ke, 2020. "Markov-based solution for information diffusion on adaptive social networks," Applied Mathematics and Computation, Elsevier, vol. 380(C).
    2. Xu, Zhaowen & Su, Hongye & Shi, Peng & Wu, Zheng-Guang, 2019. "Asynchronous H∞ control of semi-Markov jump linear systems," Applied Mathematics and Computation, Elsevier, vol. 349(C), pages 270-280.
    3. 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).
    4. Shi, Kaibo & Wang, Jun & Zhong, Shouming & Zhang, Xiaojun & Liu, Yajuan & Cheng, Jun, 2019. "New reliable nonuniform sampling control for uncertain chaotic neural networks under Markov switching topologies," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 169-193.
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    Cited by:

    1. Zheng, Xiaoyuan & Kang, Yu & Li, Hongyi & Li, Jitao, 2023. "Multiple description encoding-decoding-based resilient filtering for complex networks under the round-Robin protocol," Applied Mathematics and Computation, Elsevier, vol. 458(C).
    2. Mourad Kchaou & Mohamed Amin Regaieg, 2023. "Event-Triggered Extended Dissipativity Fuzzy Filter Design for Nonlinear Markovian Switching Systems against Deception Attacks," Mathematics, MDPI, vol. 11(9), pages 1-27, April.

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