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Structure identification of unknown complex-variable dynamical networks with complex coupling

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  • Yan, Jiaye
  • Zhou, Jiaying
  • Wu, Zhaoyan

Abstract

Topology structure and system parameters play a key role in evolving behavior of dynamical networks. Due to the complexity of dynamical networks, topology structure and system parameters are sometimes unknown or uncertain in advance. Therefore, structure identification is a necessary and critical issue. In this paper, we consider the structure identification of unknown complex-variable dynamical networks with complex coupling. Further, we design corresponding network estimators using the adaptive control scheme. Finally, we derive two results based on the Barbalat’s lemma and illustrate them by two numerical examples.

Suggested Citation

  • Yan, Jiaye & Zhou, Jiaying & Wu, Zhaoyan, 2019. "Structure identification of unknown complex-variable dynamical networks with complex coupling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 256-265.
    • Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:256-265
    DOI: 10.1016/j.physa.2019.03.064
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    References listed on IDEAS

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    Cited by:

    1. Zheng, Ying & Wu, Yayong & Jiang, Guo-Ping, 2024. "Exploring synchronizability of complex dynamical networks from edges perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).

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