IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2025i13p2190-d1695006.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/13/2190/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/13/13/2190/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiongfeng Deng & Yiqing Huang & Lisheng Wei, 2022. "Adaptive Fuzzy Command Filtered Finite-Time Tracking Control for Uncertain Nonlinear Multi-Agent Systems with Unknown Input Saturation and Unknown Control Directions," Mathematics, MDPI, vol. 10(24), pages 1-22, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Daniel Doz & Darjo Felda & Mara Cotič, 2023. "Demographic Factors Affecting Fuzzy Grading: A Hierarchical Linear Regression Analysis," Mathematics, MDPI, vol. 11(6), pages 1-19, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:13:y:2025:i:13:p:2190-:d:1695006. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.