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Pinning outer synchronization of partially coupled dynamical networks with complex inner coupling matrices

Author

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  • Li, Xuechen
  • Wang, Nan
  • Lu, Jianquan
  • Alsaadi, Fuad E.

Abstract

This paper investigates outer synchronization of partially coupled dynamical networks with complex inner coupling matrices via pinning impulsive controller. At first, we establish more realistic drive–response partially coupled networks, where the inner coupling matrices between coupled nodes can be non-full rank and also asymmetric. Then, a weighted-norm-based method is given to select the nodes that should be pinning controlled, and our synchronization criteria derived by this method can be proved to be less conservative. By using the regrouping method and our new average impulsive interval method, some efficient and less conservative synchronization criteria are derived. Our results show that the outer synchronization can be achieved by impulsively controlling a crucial fraction of nodes in the response network. Finally, numerical examples are exploited to illustrate the effectiveness of our theoretical results.

Suggested Citation

  • Li, Xuechen & Wang, Nan & Lu, Jianquan & Alsaadi, Fuad E., 2019. "Pinning outer synchronization of partially coupled dynamical networks with complex inner coupling matrices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 497-509.
    • Handle: RePEc:eee:phsmap:v:515:y:2019:i:c:p:497-509
    DOI: 10.1016/j.physa.2018.09.095
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    References listed on IDEAS

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    Cited by:

    1. Lin, Hai & Wang, Jingcheng, 2022. "Pinning synchronization of complex networks with time-varying outer coupling and nonlinear multiple time-varying delay coupling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    2. Yanjie Ji & Zhaoyan Wu, 2021. "Outer Synchronization of Complex-Variable Networks with Complex Coupling via Impulsive Pinning Control," Mathematics, MDPI, vol. 9(17), pages 1-10, September.
    3. Huang, Zhengguo & Xia, Jianwei & Wang, Jing & Wang, Jian & Shen, Hao, 2020. "Observer-based finite-time bounded analysis for switched inertial recurrent neural networks under the PDT switching law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).

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