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Finite-horizon optimal herdability control for hierarchical linear multi-agent systems with signed weighted graphs

Author

Listed:
  • Xiang, Aoxue
  • Zhao, Xinyuan
  • Ma, Ruicheng

Abstract

This paper studies the optimal herdability control for a class of hierarchical linear multi-agent systems (MASs). Unlike existing work, the finite-horizon herdability problem is presented of hierarchical MASs, which is an extension of classical controllability. Firstly, agents perform local actions in the lower layer, which are integrated into the overall system through connections between agents in the upper layer. Using this hierarchical system structure, a sufficient condition can be constructed to constrain the lower bound of all agents. Then, based on this sufficient condition, an optimal herdability controller is designed to achieve finite-horizon herdability for the hierarchical MASs. The optimal herdability control algorithms for hierarchical MASs are proposed in both discrete-time and continuous-time cases, respectively. Finally, three examples are provided to show the effectiveness of the proposed results.

Suggested Citation

  • Xiang, Aoxue & Zhao, Xinyuan & Ma, Ruicheng, 2026. "Finite-horizon optimal herdability control for hierarchical linear multi-agent systems with signed weighted graphs," Applied Mathematics and Computation, Elsevier, vol. 514(C).
    • Handle: RePEc:eee:apmaco:v:514:y:2026:i:c:s0096300325005661
    DOI: 10.1016/j.amc.2025.129841
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    References listed on IDEAS

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    1. Han, Chenglin & Qin, Kaiyu & Shi, Mengji & Liu, Yan & Li, Weihao & Lin, Boxian, 2024. "Prescribed time bipartite output consensus tracking for heterogeneous multi-agent systems with external disturbances," Applied Mathematics and Computation, Elsevier, vol. 469(C).
    2. Li, Hongchao & Niu, Guowei & Chen, Yining, 2024. "Fixed-time consensus of leader-following multi-agent systems subject to failed follower: Reconstructed topology approach," Applied Mathematics and Computation, Elsevier, vol. 482(C).
    3. Jeong, Juyoung & Lim, Yongdo & Parivallal, Arumugam, 2023. "An asymmetric Lyapunov-Krasovskii functional approach for event-triggered consensus of multi-agent systems with deception attacks," Applied Mathematics and Computation, Elsevier, vol. 439(C).
    4. Meng, Hao & Pang, Denghao & Cao, Jinde & Guo, Yechen & Niazi, Azmat Ullah Khan, 2024. "Optimal bipartite consensus control for heterogeneous unknown multi-agent systems via reinforcement learning," Applied Mathematics and Computation, Elsevier, vol. 476(C).
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