Research on Virtual Coupled Train Control Method Based on GPC & VAPF

Improving transportation efficiency is an eternal research hotspot in rail transit system. In recent years, the train operation control method based on virtual coupling has attracted the attention of many scholars. The method of train coordination and anti-collision control is not only the key to realize the virtual coupling of train, but also the key to ensure the safety of train operation. Therefore, based on the existing research, a virtual coupled train dynamics model with nonlinear dynamics is established. Then, the parameters of the operation process model of the nonlinear virtual coupled train are identified by the recursive least squares method based on real-time data, which is applied to the variable parameter artificial potential field (VAPF) for parameter identification. A fusion controller based on feature-based generalized model prediction (GPC) and VAPF is used to control the virtual coupled train and prevent collision. Finally, the validity of the proposed method is verified by using real high-speed railway data.