交通运输工程与信息学报2025，Vol.23Issue(2)：150-160,11.DOI:10.19961/j.cnki.1672-4747.2024.11.002
基于鲁棒分层控制的虚拟编组列车动态解编方法
Dynamic deprogramming approach for virtual coupled trains based on robust hierarchical control
摘要
Abstract
[Background]Owing to the application of virtual coupled-train technology,the dynamic decoupling of trains in switch segments has become a critical issue for ensuring system safety and ef-ficiency.However,existing control methods struggle to address uncertainty and external disturbances simultaneously,thus resulting in compromised control precision and stability.[Objective]This study proposes a robust hierarchical control method to improve the operational efficiency and stability of virtual coupled trains during the dynamic decoupling of switch segments.[Methods]Based on a comprehensive analysis of the dynamic operation process and constraints related to virtual coupled trains,a hierarchical control framework is designed in this study.The upper layer uses a linear qua-dratic regulator model to determine the optimal strategy for trains to pass through the switch-through optimization,whereas the lower layer employs a tube-based model predictive control(MPC)method to execute the upper-layer strategy in real time while effectively addressing uncertainty and external disturbances.[Results]Compared with the conventional MPC method,the proposed method im-proves the speed and position control accuracies by approximately 7.5%and 20.5%,respectively,as shown by simulation results.[Conclusions]The experimental results validate the effectiveness of the hierarchical control strategy and demonstrate the robustness and superiority of tube-based MPC in complex scenarios,thus providing an effective solution for the dynamic decoupling of virtual cou-pled trains in switch segments.关键词
城市交通/道岔列车控制/基于管的模型预测控制/虚拟编组/鲁棒性Key words
urban traffic/turnout train control/Tube-based MPC/virtual coupled/robustness分类
交通运输引用本文复制引用
朱才梵,王悉,杨欣,吴建军..基于鲁棒分层控制的虚拟编组列车动态解编方法[J].交通运输工程与信息学报,2025,23(2):150-160,11.基金项目
国家自然科学基金面上项目(52472334) （52472334）
中国国家铁路集团有限公司科技研究开发计划资助项目(K2023X013) （K2023X013）
北京市自然科学基金资助项目(L241051) （L241051）
