In this paper, a multi-algorithm-fusion-based cooperative tracking control strategy is proposed for high-speed trains to achieve the control objectives of reference speed trajectory tracking and adjacent safety distance maintenance simultaneously. First, the multiple high-speed train (MHST) system is formulated as a multi-agent system (MAS) with a virtual leader. Second, a coordination controller that considers the dynamic tracking performance and input saturation is designed by combining the MAS leader-follower consensus algorithm and the improved artificial potential field (APF) method. In addition, within the train-to-train (T2T) communication network, an event-triggered mechanism is introduced in the continuous state transmission process to address the communication channel capacity protection limitation issue. Third, the closed-loop stability of the MHST system is ensured by the comprehensive analysis of a novel log-type Lyapunov function. Finally, the effectiveness of the proposed event-triggered cooperative tracking control strategy is verified through a numerical example of the MHST system on a typical line.


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    Title :

    An artificial potential field approach for event-triggered cooperative control of multiple high-speed trains with free initial states


    Additional title:

    Y. ZHANG ET AL.
    INTERNATIONAL JOURNAL OF RAIL TRANSPORTATION


    Contributors:
    Zhang, Yusha (author) / Huang, Deqing (author) / Wu, Yue (author) / Zhu, Lei (author) / Chen, Yong (author)

    Published in:

    Publication date :

    2025-07-04


    Size :

    24 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English