永磁同步直线电机位置误差迭代学习补偿控制研究

Research on Iterative Learning Compensation Control of Position Error of Permanent Magnet Synchronous Linear Motor

永磁同步直线电机在执行具有重复特性的跟踪控制任务时,系统的位置误差也会出现周期性变化。针对这一问题,提出一种基于离线迭代学习补偿优化直线电机位置输入信号的控制策略。通过离线迭代学习,对直线电机系统的干扰进行迭代学习控制。对凸轮轴轨迹和正弦曲线轨迹进行迭代学习,实现对永磁直线电机运动轨迹的跟踪控制,减小直线电机的跟踪误差。实验结果表明:通过离线迭代学习控制产生的位置输入信号跟随误差较小,能很好地消除由于跟踪滞后造成的位置误差。

When a permanent magnet synchronous linear motor performs a tracking control task with repetitive characteristics, the position error of the system also changes periodically. Aimed at this problem, a control strategy based on offline iterative learning compensation to optimize the linear motor position input signal was proposed. The interference of the linear motor system was carried out through offline iterative learning. Iterative learning of camshaft trajectory and sin curve trajectory was carried out to realize the tracking control of the permanent magnet linear motor motion trajectory and reduce the tracking error of the linear motor. The experimental results show that the position input signal following error generated by off line iterative learning control is small, and the position error caused by tracking lag is well eliminated.