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Practical time-boundary consensus for fractional-order multi-agent systems under well-known and estimable topology

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  • Qing, Nengneng
  • Yang, Yongqing
  • Luan, Xiaoli
  • Wan, Haiying

Abstract

A framework for multi-agent systems with single-integrator dynamics to achieve practical fixed-time consensus has been developed under a well-known topology. However, the disagreement boundary in which is influenced by the initial values of the system. To avoid this, a practical time-boundary (PTB) consensus framework using a novel time-boundary-base generator (TBBG) is proposed in this paper, and it is extended to fractional-order multi-agent systems and estimable topology. A significant fractional differential equation is solved as the theoretical basis to achieve PTB consensus. Evolving from the time-base generator, this novel TBBG inherits the benefit of reducing the initial control input and saves energy consumption by optimizing four newly added adjustable parameters compared to the existing work. Additionally, outcomes are extended to quasi-PTB consensus and PTB-cluster consensus. The effectiveness and superiorities of the proposed approach are illustrated by two numerical examples.

Suggested Citation

  • Qing, Nengneng & Yang, Yongqing & Luan, Xiaoli & Wan, Haiying, 2024. "Practical time-boundary consensus for fractional-order multi-agent systems under well-known and estimable topology," Applied Mathematics and Computation, Elsevier, vol. 464(C).
    • Handle: RePEc:eee:apmaco:v:464:y:2024:i:c:s0096300323005696
    DOI: 10.1016/j.amc.2023.128400
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    References listed on IDEAS

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    1. Wu, Zhengtian & Gao, Qing & Jiang, Baoping & Karimi, Hamid Reza, 2021. "Solving the production transportation problem via a deterministic annealing neural network method," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    2. Huang, Jingyang & Jia, Wei & Wan, Tongxin & Xiao, Shuyi & Wang, Liqi & Dong, Jiuxiang, 2023. "Adaptive event-triggered fault-tolerant consensus of linear heterogeneous multiagent systems via hierarchical approach," Applied Mathematics and Computation, Elsevier, vol. 447(C).
    3. Du, Feifei & Lu, Jun-Guo, 2021. "New criterion for finite-time synchronization of fractional order memristor-based neural networks with time delay," Applied Mathematics and Computation, Elsevier, vol. 389(C).
    4. Fan, Yanyan & Jin, Zhenlin & Luo, Xiaoyuan & Guo, Baosu, 2022. "Robust finite-time consensus control for Euler–Lagrange multi-agent systems subject to switching topologies and uncertainties," Applied Mathematics and Computation, Elsevier, vol. 432(C).
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