考虑列车追踪的自动驾驶控制算法

王鹏玲; 王青元; 崔恒斌; 马磊; 冯晓云

doi:10.3969/j.issn.0258-2724.2013.06.012

考虑列车追踪的自动驾驶控制算法

doi: 10.3969/j.issn.0258-2724.2013.06.012

基金项目:

十一五国家科技支撑计划资助项目（2009BAG12A05）

详细信息

作者简介:
王鹏玲（1989-），女，博士研究生，研究方向为列车运行控制及其群控理论，E-mail：xnwangpengling@163.com

通讯作者:
马磊（1972-），男，教授，博士，研究方向为控制理论及其在机电系统、机器人和新能源系统等领域的应用，E-mail：malei@swjtu.edu.cn

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出版历程
- 收稿日期: 2012-09-06
- 刊出日期: 2013-12-25

Automatic Train Control Algorithm for Train Tracking

摘要

摘要: 为了研究追踪列车安全、平稳的操纵策略，在分析列车间相互纵向动力学关系的基础上，提出了列车追踪模型. 列车在不同情况下控制目标有所不同：单独运行模式下以最优速度模式曲线运行，追踪运行模式下保证安全追踪间隔运行.为了实现不同的控制目标，采用模型预测控制的分层结构，结合二次型优化算法实现最优列车速度控制.以CRH2型列车、武广线为例验证该模型的有效性. 仿真结果表明，本文方法可使追踪列车安全性得到有效提高，且当使加速度控制在-0.75~0.5 m/s2之间，加加速度控制在-0.5~0.5 m/s3之间时，乘车舒适性得到了有效的保障.
- 列车自动控制 /
- 模型预测控制 /
- 列车追踪
Abstract: To build a safe and stable operation strategy for train tracking, a train tracking model was established by the train longitudinal dynamics. In the model, control objectives of the train operation differ between single-and multi-train operation: In the single train operation, the train runs on a curve at the optimal speed; in the train-tracking operation, a safe headway between trains should be guaranteed. A hierarchical model-predictive controller together with quadratic optimization was applied to determine the optimal speed regulation process. A simulation was conducted based on the CRH2 EMU and the Wuhan-Guangzhou railway line to verify the model's validity. The results show that the train tracking security is significantly improved by the proposed method, and the riding comfort is guaranteed while the acceleration is at -0.75-0.5 m/s2 and the jerk is at -0.5-0.5 m/s3.
- automatic train control /
- model predictive control /
- train tracking

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