Distributed model predictive control for real-time train regulation of metro line based on Dantzig-Wolfe decomposition
Document Type
Journal Article
Publication Date
2023
Subject Area
mode - subway/metro, place - urban, technology - intelligent transport systems
Keywords
Metro lines, train regulation, distributed MPC, Dantzig-Wolfe decomposition
Abstract
This paper aims to propose a novel distributed model predictive control (MPC) scheme for real-time train regulation in urban metro transportation. Particularly, a nonlinear real-time train regulation model is put forward to minimize the timetable deviations and the control strategies for each trainunder the uncertain disturbances, which is then reformulated into a linear optimization model for easy to solve. By regarding each train as a subsystem, we design the distributed MPC algorithm based on the Dantzig-Wolfe decomposition for the train regulation problem, which decomposes the original optimization problem into numerous smaller and less complicated optimization control problems that can be solved independently. Under the distributed mechanism, we regard each train as a local subsystem, which only interacts with the coordinator, ensuring the flexibility and modularity of the control structure. Numerical cases are provided to demonstrate the effectiveness and robustness of the proposed distributed MPC method.
Rights
Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.
Recommended Citation
Chen, Z., Li, S., Zhang, H., Wang, Y., & Yang, L. (2023). Distributed model predictive control for real-time train regulation of metro line based on Dantzig-Wolfe decomposition. Transportmetrica B: Transport Dynamics, 11(1), 408-433.
