TY - GEN
T1 - Cooperative Control for Multiple Trains with Prescribed Performance and Collision Avoidance Guarantees
AU - Zheng, Yue
AU - Bai, Weiqi
AU - Dong, Hairong
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This paper aims to present a cooperative control method to improve the tracking accuracy and safety of multiple trains under uncertain system environment. In the controller design, prescribed performance functions are devised to restrict global tracking errors and guarantee the transient and steady-state performance of each train. An active security protection control framework is designed based on the technique of integrating terminal sliding mode, enabling the trains to reach state consensus quickly in finite time and guaranteeing the inter-train distances always to be within the safe range. The radial basis function neural network is adopted to approximate the time-varying running resistance of the trains. Consequently, the cooperative control method is established under which the multiple-train system achieves state consensus with specified performance and collisions avoidance guarantees during the train status adjustment process. Finally, rigorous mathematical analysis is provided and experimental simulations are conducted to jointly demonstrate the effectiveness and feasibility of the proposed theoretical results.
AB - This paper aims to present a cooperative control method to improve the tracking accuracy and safety of multiple trains under uncertain system environment. In the controller design, prescribed performance functions are devised to restrict global tracking errors and guarantee the transient and steady-state performance of each train. An active security protection control framework is designed based on the technique of integrating terminal sliding mode, enabling the trains to reach state consensus quickly in finite time and guaranteeing the inter-train distances always to be within the safe range. The radial basis function neural network is adopted to approximate the time-varying running resistance of the trains. Consequently, the cooperative control method is established under which the multiple-train system achieves state consensus with specified performance and collisions avoidance guarantees during the train status adjustment process. Finally, rigorous mathematical analysis is provided and experimental simulations are conducted to jointly demonstrate the effectiveness and feasibility of the proposed theoretical results.
KW - Cooperative control
KW - RBF neural network
KW - multiple high-speed trains
KW - prescribed performance control
UR - https://www.scopus.com/pages/publications/85195791632
U2 - 10.1109/ICIT58233.2024.10540713
DO - 10.1109/ICIT58233.2024.10540713
M3 - 会议稿件
AN - SCOPUS:85195791632
T3 - Proceedings of the IEEE International Conference on Industrial Technology
BT - ICIT 2024 - 2024 25th International Conference on Industrial Technology
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE International Conference on Industrial Technology, ICIT 2024
Y2 - 25 March 2024 through 27 March 2024
ER -