Research on EMPC for multi-objective optimal control of high-speed trains under parametric uncertainty

• Main Authors: Cheng, Junshu, Sun, Pengfei, Wang, Qingyuan, Feng, Xiaoyun
• Format: Conference Proceeding
• Language: English
• Published: SPIE 20.02.2024
• ISBN: 1510674462; 9781510674462
• ISSN: 0277-786X
• DOI: 10.1117/12.3015754

The train operations are subject to several uncertain factors, which pose challenges to achieving the train’s multi-objective optimal control. To improve the service quality and transportation efficiency of high-speed railways, this paper proposes a control method to realize the multi-objective operation of high-speed trains in terms of safety, punctuality, energy efficiency, and driving smoothness considering the uncertainty. Firstly, by studying the kinematic model under uncertainty and operational constraints of the train, and combining them with multi-objective optimization theory, an optimal control model for the multi-objective operation of high-speed trains is established. Secondly, to solve the optimal control problem under the uncertainty, the nonlinear and non-convex optimal control problem for multi-objective operations of the train is reformulated as a robust economic model predictive control framework, which is then convexified into a computationally tractable convex model, and then the corresponding algorithm is designed to give the solutions. Finally, the proposed method is validated through simulation on a real high-speed rail line, and compared with tracking-type robust model predictive control. The simulation results demonstrate that the proposed method is capable of achieving safe, punctual, energy-efficient, and smooth operation of high-speed trains in the presence of uncertain factors.