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Finite-time stochastic synchronization of dynamic networks with nonlinear coupling strength via quantized intermittent control

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  • Zhou, Ya
  • Wan, Xiaoxiao
  • Huang, Chuangxia
  • Yang, Xinsong

Abstract

This paper considers the finite-time synchronization of dynamic networks with nonlinear coupling strength and stochastic perturbations by using intermittent control. Since it is difficult to estimate the settling-time due to the uncertain intermittent intervals, a novel lemma is established. Then, two quantized intermittent controllers without chattering are designed, which can reduce the control cost and save channel resources. T-S fuzzy method is utilized to deal with the nonlinear coupling strength. By using Lyapunov direct method, sufficient conditions formulated by linear matrix inequalities (LMIs) are derived to ensure that the considered system can realize finite-time synchronization. Moreover, the control gains are designed. Two numerical simulations are given to show the merits of theoretical analysis.

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  • Zhou, Ya & Wan, Xiaoxiao & Huang, Chuangxia & Yang, Xinsong, 2020. "Finite-time stochastic synchronization of dynamic networks with nonlinear coupling strength via quantized intermittent control," Applied Mathematics and Computation, Elsevier, vol. 376(C).
    • Handle: RePEc:eee:apmaco:v:376:y:2020:i:c:s0096300320301260
    DOI: 10.1016/j.amc.2020.125157
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    References listed on IDEAS

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    Cited by:

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    7. Zhou, Lili & Zhang, Yuhao & Tan, Fei & Huang, Mingzhe, 2023. "Adaptive secure synchronization of complex networks under mixed attacks via time-controllable technology," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    8. Zhang, Wanli & Yang, Xinsong & Yang, Shiju & Alsaedi, Ahmed, 2021. "Finite-time and fixed-time bipartite synchronization of complex networks with signed graphs," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 188(C), pages 319-329.
    9. Jiang, Ziling & Huang, Fan & Shao, Haijian & Cai, Shuiming & Lu, Xiaobo & Jiang, Shengqin, 2023. "Time-varying finite-time synchronization analysis of attack-induced uncertain neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).

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