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A Prescribed-Time Consensus Algorithm for Distributed Time-Varying Optimization Based on Multiagent Systems

Author

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  • Yanling Zheng

    (School of Science, Zhejiang University of Science and Technology, Hangzhou 310023, China)

  • Siyu Liu

    (College of Engineering, Zhejiang Normal University, Jinhua 321004, China)

  • Jie Zhong

    (College of Mathematics and Computer Science, Zhejiang Normal University, Jinhua 321004, China)

Abstract

This paper presents a distributed optimization algorithm for time-varying objective functions utilizing a prescribed-time convergent multi-agent system within undirected communication networks. Departing from conventional time-invariant optimization paradigms with static optimal solutions, our approach specifically addresses the challenge of tracking dynamic optimal trajectories in evolving environments. A novel continuous-time distributed optimization algorithm is developed based on prescribed-time consensus, guaranteeing the consensus attainment among agents within a user-defined timeframe while asymptotically converging to the time-dependent optimal solution. The proposed methodology enables explicit predetermination of convergence duration, representing a significant advancement over existing asymptotic convergence methods. Moreover, two simulation examples on the rendezvous problem and multi-robots control are presented to validate the theoretical results, exhibiting precise time-controlled convergence characteristics and effective tracking performance for time-varying optimization targets.

Suggested Citation

  • Yanling Zheng & Siyu Liu & Jie Zhong, 2025. "A Prescribed-Time Consensus Algorithm for Distributed Time-Varying Optimization Based on Multiagent Systems," Mathematics, MDPI, vol. 13(13), pages 1-13, July.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:13:p:2190-:d:1695006
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