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基于迭代学习控制的列车自动运行研究
引用本文:王 娟,李国宁,刘雨佳. 基于迭代学习控制的列车自动运行研究[J]. 计算机工程与应用, 2014, 50(9): 219-224
作者姓名:王 娟  李国宁  刘雨佳
作者单位:兰州交通大学 自动化与电气工程学院,兰州 730070
摘    要:针对列控系统难以建立精确的动力学模型问题,利用列车运行过程中包含的大量重复信息,选用迭代学习算法对列车动力学模型中的未知参数进行辨识并提出基于迭代学习控制的列车自动运行控制算法。算法核心是利用历史数据生成新的控制量控制列车自动运行。仿真结果表明,经过一定次数的迭代,参数辨识值保持稳定并且列车能够严格跟踪目标曲线行驶,保证列车高精度、高平稳、高安全的运行。

关 键 词:列车自动运行  迭代学习辨识  迭代学习控制  学习律  

Study on automatic train operation based on iterative learning control
WANG Juan,LI Guoning,LIU Yujia. Study on automatic train operation based on iterative learning control[J]. Computer Engineering and Applications, 2014, 50(9): 219-224
Authors:WANG Juan  LI Guoning  LIU Yujia
Affiliation:School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Abstract:Aiming for the difficulty to establish accurate dynamic model for train control system, and combining a large number of duplicate information contained in the train operation, the unknown parameters in the train dynamics model are identified by using Iterative Learning Control(ILC)algorithm and a control algorithm based on ILC is proposed to control the train. The core of the algorithm is the use of historical data to generate a new input to control train. The simulation results show that after a certain number of iterations, parameters identification value remains stable and the train can strictly follow the target curve to run and ensure the train can travel with high-precision, high-steady and high-security.
Keywords:automatic train operation  iterative learning identification  iterative learning control  learning law
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