基于迭代学习控制的列车自动运行研究

Study on automatic train operation based on iterative learning control

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。

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.