基于自抗扰控制的地铁列车驾驶控制算法

Subway Train Driving Control Algorithm Based on Active Disturbance Rejection Control

基于PID算法或基于模糊PID算法的地铁列车ATO驾驶控制算法的速度响应误差大,加减速切换频繁,从而导致旅客舒适度一般,列车停车精度不高,列车能耗略高和运行时间存在一定误差的问题。搭建地铁列车模型,结合北京地铁亦庄线线路数据,通过仿真实验对比基于PID算法,基于模糊PID算法,基于专家系统,基于ADRC算法的地铁列车ATO驾驶控制算法的控制效果,并在实验中运用改进的粒子群算法对ADRC算法的参数进行快速整定。仿真结果表明:基于ADRC算法的地铁列车ATO驾驶控制算法的控制效果优于基于PID算法和基于模糊PID算法的地铁列车ATO驾驶控制算法,其控制效果和经验丰富的司机驾驶基本相当,可以有效提高旅客舒适度、列车停车精度,减小列车能耗、运行时间误差。

The ATO driving control algorithm based on PID algorithm or fuzzy PID algorithm has large speed response error and frequent acceleration and deceleration switching, which leads to poor passenger comfort, low parking accuracy, high energy consumption and certain running time error. In this paper, a subway train model is constructed. Combined with the data of Yizhuang metro line, the control effect of ATO driving control algorithm based on PID algorithm, fuzzy PID algorithm, expert system and ADRC algorithm is compared through simulation experiments. The parameters of ADRC algorithm are quickly processed by improved particle swarm optimization algorithm. The simulation results show that the control effect of the ATO driving control algorithm based on ADRC is better than that of the subway train ATO driving control algorithm based on PID algorithm and fuzzy PID algorithm, and it is basically the same as that by experienced drivers, which can effectively improve passenger comfort and train parking accuracy, and reduce train energy consumption and running time error.