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Intermittent control for identifying network topology

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  • Wu, Zhaoyan

Abstract

Topology embodies the structure complexity of dynamical network coupled with interactive individuals and plays a key role in its evolution dynamics. In many practical applications, the topology is assumed to be exactly known. How to identify the unknown topology effectively is always a challenging and important issue. In this paper, we mainly consider the intermittent control for identifying topology of both undirected network and balanced network. The corresponding network estimators with intermittent controllers and novel piecewise parameter updating laws are proposed and the sufficient conditions are derived. Further, we discuss the topology identification of general network under certain assumption.

Suggested Citation

  • Wu, Zhaoyan, 2024. "Intermittent control for identifying network topology," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
    • Handle: RePEc:eee:chsofr:v:179:y:2024:i:c:s0960077924000274
    DOI: 10.1016/j.chaos.2024.114476
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    References listed on IDEAS

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    1. Peyman Razmi & Mahdi Ghaemi Asl & Giorgio Canarella & Afsaneh Sadat Emami, 2021. "Topology identification in distribution system via machine learning algorithms," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-20, June.
    2. Yuanzhi Yang & Lei Yu & Xing Wang & Siyi Chen & You Chen & Yipeng Zhou, 2020. "A novel method to identify influential nodes in complex networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 31(02), pages 1-14, February.
    3. Wang, Xiao Fan & Chen, Guanrong, 2002. "Pinning control of scale-free dynamical networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 310(3), pages 521-531.
    4. Zhao, Jie & Wang, Yunchuan & Deng, Yong, 2020. "Identifying influential nodes in complex networks from global perspective," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
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