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

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.

KEYWORDS:

• Cooperative tracking control
• high-speed trains
• multi-agent system (MAS)
• artificial potential field (APF)
• event-triggered mechanism

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was partially supported by the National Natural Science Foundation of China [grant numbers U21A20169, 62303383], the Sichuan Science and Technology Program [grant number 2024NSFSC1493], and the Fundamental Research Funds for the Central Universities [grant number 2682024CX008].