永磁直线同步电机自适应PD型迭代学习控制

针对永磁直线同步电机伺服系统易受摩擦力、端部效应和测量扰动等不确定因素影响的问题,提出一种自适应PD型迭代学习控制方法.该控制方法根据误差的大小在线智能地调整学习增益,从而抑制扰动,并在控制器的微分系数上引入指数学习增益,实现收敛速度与跟踪精度之间的折衷;从理论上证明了自适应PD型ILC的收敛性,分析了该控制算法的优越性.结果表明,与传统PD型ILC相比,自适应PD型ILC具有更快的收敛速度和更强的鲁棒性,大大地减小了跟踪误差.

Adaptive PD-type iterative learning control for permanent magnet linear synchronous motor

In order to solve the problem that the servo system of permanent magnet linear synchronous motor （PMLSM） is easily affected by such uncertainty factors as friction, end effect and measurement disturbance,〖JP〗 an adaptive PD type iterative learning control （ILC） method was proposed. According to the size of the error, the control method could intelligently adjust the learning gain so as to restrain the disturbance. Simultaneously, the exponential learning gain was introduced for the differential coefficient, which could achieve the compromise between both convergence rate and tracking precision. The convergence of adaptive PD type ILC was theoretically proved, and the superiority of the proposed control algorithm was analyzed. The results indicate that compared with the traditional PD type ILC, the adaptive PD type ILC has faster convergence rate and stronger robustness, and can greatly reduce the tracking error.