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【背景】随着虚拟编组列车在道岔区段动态解编场景的复杂化，突发扰动事件下的协同失控风险显著增加。现有方法因缺乏故障响应闭环机制与动态安全约束保障，难以同时应对系统异常和不确定性干扰，威胁列车运行安全。【目标】构建面向突发事件的闭环控制理论，通过实时检测与动态控制重构，实现多列车安全轨迹的协同优化，提升运行控制的鲁棒性与安全性。【方法】基于残差检测与双层目标切换机制，提出动态鲁棒管模型预测控制框架：上层通过残差观测器实时捕捉系统异常，触发目标切换并生成安全轨迹；下层采用动态鲁棒管收缩律，通过在线滚动优化生成抗扰控制序列，确保多列车状态轨迹严格位于安全不变集内。【结果】相较于传统模型预测控制方法，所提方法在事故场景下速度与位置跟踪精度平均提升65%和59%，且计算效率满足实时性要求，验证了其在复杂扰动场景下的有效性。【结论】通过故障检测-目标切换-鲁棒控制的全流程覆盖，为解决虚拟编组列车动态解编协同失控难题提供了系统化方案，为城市轨道交通运营安全提供了理论支撑。
Abstract：[Background] With the increasing complexity of dynamic disbandment scenarios for virtual-coupled trains in turnout sections， the risk of coordinated loss of control in the presence of unexpected disturbances has risen markedly. Current methods， lacking closed-loop mechanisms for fault response and dynamic safety constraint enforcement， are insufficient to handle system anomalies and uncertainties concurrently， thus posing risks to train operational safety. [Objective] To develop a closed-loop control framework tailored for unexpected events， enabling coordinated optimization of multi-train safety trajectories through real-time detection and dynamic control reconstruction， thus improving the robustness and safety of train operations. [Methods] A dynamic robust tube model predictive control (MPC) framework is proposed， incorporating residual detection and a two-tier objective switching mechanism: the upper tier employs a residual observer for real-time anomaly detection， which triggers objective transitions and generates safe trajectories; the lower tier applies a dynamic robust tube contraction strategy， producing disturbance-rejecting control sequences through online receding horizon optimization， thereby guaranteeing that all multi-train state trajectories are strictly confined within the safe invariant set. [Result] Compared to traditional model predictive control approaches， the proposed method yields average improvements of 65% in speed tracking accuracy and 59% in position tracking accuracy under accident scenarios， with computational efficiency meeting real-time requirements. The effectiveness of this approach in complex disturbance scenarios is validated. [Conclusion] By integrating fault detection， objective switching， and robust control into a unified process， this study offers a systematic solution to the challenge of coordinated loss of control in dynamic virtual train disbandment， thereby furnishing theoretical foundations for the safe operation of urban rail transit systems.
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基本信息:
DOI：10.19961/j.cnki.1672-4747.2025.08.029
中图分类号:U284.48
引用信息:
[1]何若冰,朱才梵,冯文件,等.基于目标切换机制的分布式多列车鲁棒预测控制[J].交通运输工程与信息学报().DOI:10.19961/j.cnki.1672-4747.2025.08.029.
基金信息:
国家自然科学基金面上项目(72331001，U2469201)
2025-10-17
2025-10-17
2025-10-17