A Robust Control Method Based on Artificial Potential Field for the Virtually Coupled Train Set

The transport capacity of the railway system does not match the increasing passenger demand, which calls for capacity enhancements as urban connectedness rises. A new railway signaling technique, i.e., virtual coupling, has the potential to increase transport capacity. This paper aims to tackle the difficulties associated with preserving the stability and robustness of a virtually coupled train set (VCTS) during disturbed conditions. Based on the train coupling relationship and communication architecture, the train dynamic model and state-space equations are constructed, taking into account parameter uncertainty. Subsequently, a robust $H_{\infty}$ controller with an artificial potential field control term is developed and solved using the linear matrix inequalities approach. To validate the controller's effectiveness, a case study is conducted utilizing the Beijing-Shanghai high-speed railway data from Langfang station to Tianjin station. This simulation results show that the VCTS could swiftly return to a stable state in the presence of external disturbances and initial errors, ensuring the VCTS's stability and robustness.