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【背景】随着虚拟编组列车技术的应用，列车在道岔区段的动态解编成为确保系统安全与效率的关键问题。然而，现有控制方法难以同时应对不确定性和外部干扰，导致列车控制精度和稳定性受到影响。【目标】本研究旨在提出一种鲁棒的分层控制方法，以提高虚拟编组列车在道岔区段动态解编过程中的运行效率和稳定性。【方法】在深入分析虚拟编组列车的动态运行过程及相关约束条件的基础上，本文设计了一个分层控制框架，上层采用线性二次优化（Linear Quadratic Regulator,LQR）模型，通过优化计算确定列车通过道岔的最优策略；下层则采用基于管的扰动模型预测控制（Tube-basedModel Predictive Control,Tube-based MPC）方法，实时执行上层策略并有效应对不确定性和外部扰动。【结果】与传统模型预测控制（MPC）方法进行对比，仿真结果表明，所提出的方法在速度控制精度上提高了约7.5%，在位置控制精度上提高了约20.5%。【结结论论】实验验证了分层控制策略的有效性，并证明了Tube-based MPC在复杂场景下的鲁棒性和优越性，为虚拟编组列车的道岔区段动态解编提供了有效的解决方案。
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 efficiency. 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 quadratic 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 improves 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 coupled trains in switch segments.
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基本信息:
DOI：10.19961/j.cnki.1672-4747.2024.11.002
中图分类号:U284.5
引用信息:
[1]朱才梵,王悉,杨欣等.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(02):150-160.DOI:10.19961/j.cnki.1672-4747.2024.11.002.
基金信息:
国家自然科学基金面上项目（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）; 北京市自然科学基金资助项目（L241051）