基于迭代学习与FIR滤波器的PMLSM高精密控制

High Precision Control for PMLSM Based on Iterative Learning and FIR Filter

针对永磁直线同步电机(PMLSM)运行时易受端部效应、摩擦力、负载扰动、参数变化等不确定性因素的影响而难以达到高精度跟踪控制的问题,提出一种基于迭代学习与有限冲击响应(FIR)滤波器的控制方案。PMLSM伺服系统执行重复任务时,迭代学习控制(ILC)可有效地抑制重复性扰动,具有很高的控制精度,但执行非重复性任务时很难获得较高的控制精度。为了进一步改善基于ILC的PMLSM伺服系统运行迭代1次的跟踪精度,利用ILC的输出信息来设计FIR滤波器,进而用FIR滤波器来代替ILC,使控制系统达到最优的ILC,以提高系统的跟踪精度。采用滑模控制(SMC)对FIR滤波器进行补充,使位置误差快速收敛到一定的界限内,以提高系统的抗扰能力。实验结果表明,所提出的控制方案使系统具有很高的位置跟踪精度和很强的鲁棒性。

For permanent magnet linear synchronous motor（ PMLSM）,the influence of the uncertain factors such as the end effect,friction,load force and parameter variation and so on were easily affected by the operation. It was very difficult to achieve high precision tracking control. A control scheme based on iterative learning and finite impulse response（ FIR） filter was proposed. Iterative learning control（ ILC） could effectively suppress the repetitive disturbances and had higher control precision for PMLSM servo system with repetitive tasks. When PMLSM implemented non-repetitive tasks,it was difficult to achieve higher control precision. In order to further improve the tracking accuracy of the system running 1 times for PMLSM servo system based on ILC,FIR filter was designed by using the output information of ILC. The well designed filter was used to replace ILC. It made the control system gain the optimal ILC. The tracking accuracy of the system was improved. The sliding mode control（ SMC） was used to supplement the FIR filter,so that the position error was fast converged to a certain limit,so as to improve the ability of disturbance rejection of the system. The experimental results indicate that the proposed control scheme makes the system have higher position tracking accuracy and stronger robustness.