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

Yusha Zhang, Deqing Huang, Yue Wu, Lei Zhu and Yong Chen

International Journal of Rail Transportation, 2025, vol. 13, issue 4, 708-731

Abstract: 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.

Date: 2025
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DOI: 10.1080/23248378.2024.2362373

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