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Event-based cluster synchronization of coupled genetic regulatory networks

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  • Yue, Dandan
  • Guan, Zhi-Hong
  • Li, Tao
  • Liao, Rui-Quan
  • Liu, Feng
  • Lai, Qiang

Abstract

In this paper, the cluster synchronization of coupled genetic regulatory networks with a directed topology is studied by using the event-based strategy and pinning control. An event-triggered condition with a threshold consisting of the neighbors’ discrete states at their own event time instants and a state-independent exponential decay function is proposed. The intra-cluster states information and extra-cluster states information are involved in the threshold in different ways. By using the Lyapunov function approach and the theories of matrices and inequalities, we establish the cluster synchronization criterion. It is shown that both the avoidance of continuous transmission of information and the exclusion of the Zeno behavior are ensured under the presented triggering condition. Explicit conditions on the parameters in the threshold are obtained for synchronization. The stability criterion of a single GRN is also given under the reduced triggering condition. Numerical examples are provided to validate the theoretical results.

Suggested Citation

  • Yue, Dandan & Guan, Zhi-Hong & Li, Tao & Liao, Rui-Quan & Liu, Feng & Lai, Qiang, 2017. "Event-based cluster synchronization of coupled genetic regulatory networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 649-665.
    • Handle: RePEc:eee:phsmap:v:482:y:2017:i:c:p:649-665
    DOI: 10.1016/j.physa.2017.04.024
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    References listed on IDEAS

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    1. Hu, Aihua & Cao, Jinde & Hu, Manfeng & Guo, Liuxiao, 2015. "Cluster synchronization of complex networks via event-triggered strategy under stochastic sampling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 434(C), pages 99-110.
    2. Guan, Zhi-Hong & Zhang, Hao, 2008. "Stabilization of complex network with hybrid impulsive and switching control," Chaos, Solitons & Fractals, Elsevier, vol. 37(5), pages 1372-1382.
    3. Michael B. Elowitz & Stanislas Leibler, 2000. "A synthetic oscillatory network of transcriptional regulators," Nature, Nature, vol. 403(6767), pages 335-338, January.
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    Cited by:

    1. Luo, Mengzhuo & Cheng, Jun & Liu, Xinzhi & Zhong, Shouming, 2019. "An extended synchronization analysis for memristor-based coupled neural networks via aperiodically intermittent control," Applied Mathematics and Computation, Elsevier, vol. 344, pages 163-182.
    2. Luo, Mengzhuo & Liu, Xinzhi & Zhong, Shouming & Cheng, Jun, 2018. "Synchronization of multi-stochastic-link complex networks via aperiodically intermittent control with two different switched periods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 20-38.
    3. Narayanan, G. & Syed Ali, M. & Karthikeyan, Rajagopal & Rajchakit, Grienggrai & Jirawattanapanit, Anuwat, 2022. "Novel adaptive strategies for synchronization control mechanism in nonlinear dynamic fuzzy modeling of fractional-order genetic regulatory networks," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).

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