Distributed Model Predictive Control Strategy for Constrained High-Speed Virtually Coupled Train Set

Virtual Coupling (VC) is regarded as a breakthrough to the traditional train operation and control for improving capability flexibility in railways. It brings benefits trains under VC are allowed operate much closer one another, forming virtually coupled set (VCTS). However, safe stable spacing between VCTS problem since there no rigid couplers connect them into fixed formation, especially high-speed scenarios. Due close spacing, interference becomes non-negligible various maneuvers of preceding can significantly affect driving behaviors following train; this results fluctuating therefore an unstable VCTS. Aiming at minimizing maintaining constantly VCTS, paper presents distributed model predictive (DMPC) approach solving problem. Particularly, proposed method focuses on feasibility stability problem, with considerations constraint safety braking distance individual constraints speed limit variations restricted traction/braking performance. To guarantee stability, terminal controller invariant DMPC designed. For rigor, sufficient conditions mathematically proved derived. Based data Beijing-Shanghai railway line, numerical experiments conducted verify correctness derived effectiveness disturbances.