基于列车模型的 ATO 超前预测优化控制算法研究

Research on ATO Advance Prediction and Optimal ControlAlgorithm Based on Train Models

摘要:

本文在总结现有 ATO 控制算法过程中，分析了制约ATO 性能提高的瓶颈点。在此基础上，针对常规 ATO 算法采用负反馈调节机制及系统本身延迟带来的系统滞后性，基于列车模型研究 ATO 的超前预测优化控制算法。算法中引入列车模型及相关线路数据，通过使用模型模拟列车运行来规划和优选 ATO 指导曲线，使用模型同步模拟的方式补偿阻力扰动偏差和系统延时偏差，提升 ATO 系统对列车本身及外在线路条件变化及时做出应变的能力。

Abstract:

This paper summarizes existing ATO control algorithms and analyzes the bottlenecks limiting improvements in AT O performance.Building on this analysis, an advanced predictive optimization control algorithm for ATO, based on a train m odel, is proposed to address system lag caused by conventional ATO algorithms employing negative feedback regulation and inherent system delays.The algorithm integrates a train model and corresponding track data to plan and optimize ATO guidance curves through train operation simulation. It compensates for resistance disturbance and system delay deviations via sy nchronous model simulation, thereby enhancing the ATO system’s responsiveness to variations in train parameters and extern al track conditions.