列车自动运行迭代学习控制算法的研究

针对列车自动运行系统,提出了新的迭代学习控制方案.为避免列车超速引发制动停车,在迭代初期设置低于计划速度曲线的期望轨迹,随着迭代次数增加,控制精度与稳定性逐渐提高,设置的期望轨迹将快速接近并保持为计划速度曲线,实现控制目标.在学习律中引入期望轨迹变化信息,实现变轨迹路径跟踪的迭代学习控制.仿真结果表明,该迭代学习控制方案能够实现变期望轨迹的跟踪,具有很快的学习速度与良好的控制性能,能够有效避免迭代初期列车速度波动导致超速紧急制动.

Research on lterative Learning Control Algorithm for Automatic Train Operation

Aiming for Automatic Train Operation(ATO) System,a new Iterative Learning Control Algorithm was presented.During the initial period,desired trajectories were set up lower than the planned speed trajectory to prevent train over speeding and triggering emergency brake.With the increased iterative times,the control accuracy and stability was increased gradually,and the desired trajectories would promptly approach and keep the same as planned speed trajectory.The variation information of desired trajectories wa...