Cooperative Control Based on Distributed Model Predictive Control Method for Urban Rail Transit

Focused on the challenge of train's high-density tracking control for urban rail transit, a cooperative control method based on Distributed Model Predictive Control (DMPC) is studied. Firstly, the force of the train is analyzed and the state space model of train operation is established. Upon this foundational framework, the control objectives of the train control system and corresponding control strategies are proposed. Secondly, to ensure the safety of train operations, the DMPC is used to design a cooperative train consistency control algorithm that considers the dynamic parameters such as the position, speed, and acceleration of the front train. The stability of the train control system is analyzed and verified by the Lyapunov stability theorem. Finally, combined with the west section of Beijing Metro Line No. 11, the proposed method is simulated and verified. The experimental results show that the proposed train cooperative control method can ensure the safe operation of trains, and make the state of trains consistent and have good synchronization. Compared with the following control method, the cooperative control method can reduce the train spacing and speed difference, increasing by 85% and 76% respectively.