Multi-Agent System Based Cooperative Control for Speed Convergence of Virtually Coupled Train Formation

• Published in: Sensors (Basel, Switzerland) Vol. 24; no. 13; p. 4231
• Main Authors: Liu, Chuanzhen, Xu, Zhongwei
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 29-06-2024
• Subjects: barrier Lyapunov function; Collaboration; Communication; Control algorithms; distributed observer; High speed rail; Methods; multi-agent systems; Simulation; speed convergence; System theory; train-formation cooperative control; Trains; Velocity; speed convergence; multi-agent systems; distributed observer; train-formation cooperative control; barrier Lyapunov function
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s24134231

This paper investigates the problem of spacing control between adjacent trains in train formation and proposes a distributed train-formation speed-convergence cooperative-control algorithm based on barrier Lyapunov function. Considering practical limitations such as communication distance and bandwidth constraints during operation, not all trains can directly communicate with the leader and obtain the expected trajectory it sends, making it difficult to maintain formation consistency as per the predetermined ideal state. Furthermore, to address the challenge of unknown external disturbances encountered by trains during operation, this paper designs a distributed observer deployed on each train in the formation. This observer can estimate and dynamically compensate for unknown reference trajectories and disturbances solely based on the states of adjacent trains. Additionally, to ensure that the spacing between adjacent trains remains within a predefined range, a safety hard constraint, this paper encodes the spacing hard constraint using barrier Lyapunov function. By integrating nonlinear adaptive control theory to handle model parameter uncertainties, a barrier Lyapunov function-based adaptive control method is proposed, which enables all trains to track the reference trajectory while ensuring that the spacing between them remains within the preset interval, therefore guaranteeing the asymptotic stability of the closed-loop system. Finally, a practical example using data from the Guangzhou Metro Line 22, specifically the route from Shiguang Road Station to Chentougang Station over three stations and two sections, is utilized to validate the effectiveness and robustness of the proposed algorithm.