基于自适应迭代学习控制的永磁同步电动机稳态转速脉动抑制策略

Speed Fluctuation Minimization Strategy of PMSM Based on Adaptive Iterative Learning Control

为了提高永磁同步电动机转速控制的性能,抑制其稳态下的转速波动,设计了一种并联于传统速度PI控制器的自适应迭代学习控制器,用于对转速波动进行补偿。针对传统迭代学习控制器对非周期信号抗扰能力差的问题,提出了Fal函数与迭代学习控制器结合的方法,保证了系统在调速时仍具备良好的响应特性;针对迭代学习控制器迭代增益系数的整定问题,提出了一种控制参数自适应的迭代学习控制方法。实验结果表明,所提出的Fal函数与迭代学习控制器结合的方法能有效提升系统的抗扰能力;同时,提出的参数自适应方案也能提升迭代学习控制器对转速波动抑制的能力。

In order to improve the performance of the PMSM speed control and restrain its steady-state speed fluctuation,an adaptive iterative learning controller parallel to the traditional speed PI controller is designed to compensate the speed fluctuation.Aiming at the problem that the traditional iterative learning controller has poor anti-disturbance ability to aperiodic signals,a method combining Fal function and iterative learning controller is proposed to ensure that the system still has good response characteristics during speed regulation.An iterative learning control method with adaptive control parameters is proposed to solve the tuning problem of iterative learning controller's iterative gain coefficient.Experimental results show that the proposed method combining Fal function and iterative learning controller can effectively improve the disturbance immunity of the system.At the same time,the proposed parameter adaptive scheme can also improve the ability of the iterative learning controller to suppress the speed fluctuation.