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Observer-based fixed-time topology identification and synchronization for complex networks via quantized pinning control strategy

Author

Listed:
  • Wu, Huaiqin
  • Zhao, Xueqing
  • Wang, Lingyan
  • Cao, Jinde

Abstract

This paper is concerned with observer-based topology identification and synchronization in fixed time for multi-weighted complex networks (MWCNs) with/without output couplings. Firstly, a new fixed-time stability criterion is developed for continuous nonlinear systems by utilizing incomplete beta function and beta function ratio. Secondly, a quantized pinning controller and several topology observers are designed respectively to realize the fixed-time topology identification (FTTI) and the fixed-time synchronization (FTS) objective. Thirdly, by applying Lyapunov functional approach, the proposed stability criteria and the inequality analysis technique, some sufficient conditions with respect to the FTTI and the FTS are addressed in terms of linear matrix inequalities (LMIs). Eventually, the Chua's chaotic circuit and the island micro-grid, as two practical application examples, are given to demonstrate the effectiveness of the designed control strategies and the correctness of the obtained theoretical results.

Suggested Citation

  • Wu, Huaiqin & Zhao, Xueqing & Wang, Lingyan & Cao, Jinde, 2025. "Observer-based fixed-time topology identification and synchronization for complex networks via quantized pinning control strategy," Applied Mathematics and Computation, Elsevier, vol. 507(C).
    • Handle: RePEc:eee:apmaco:v:507:y:2025:i:c:s0096300325002942
    DOI: 10.1016/j.amc.2025.129568
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    References listed on IDEAS

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    1. Mahmoud Saleh & Yusef Esa & Ahmed Mohamed, 2018. "Applications of Complex Network Analysis in Electric Power Systems," Energies, MDPI, vol. 11(6), pages 1-16, May.
    2. Hou, Xinzhao & Wu, Huaiqin & Cao, Jinde, 2025. "Practical finite-time synchronization for Lur'e systems with performance constraint and actuator faults: A memory-based quantized dynamic event-triggered control strategy," Applied Mathematics and Computation, Elsevier, vol. 487(C).
    3. Wang, Longjian & Zheng, Shaoya & Wang, Yonggang & Wang, Longfei, 2021. "Identification of critical nodes in multimodal transportation network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    4. Wenju Du & Yinzhen Li & Jiangang Zhang & Jianning Yu, 2019. "Synchronisation between two different networks with multi-weights and its application in public traffic network," International Journal of Systems Science, Taylor & Francis Journals, vol. 50(3), pages 534-545, February.
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