基于ILC算法的PMSM模型参考自适应矢量控制

PMSM Model Reference Adaptive Vector Control Based on Iterative Learning Control Algorithm

永磁同步电机(PMSM)在工业控制领域应用广泛,但由于PMSM转速转矩脉动大的缘故,仍很难应用于高精度运动控制领域。考虑到机械速度传感器的稳定性及系统成本问题,采用模型参考自适应系统(MRAS)控制估计电机转速,在PMSM矢量控制MRAS基础上,结合传统比例积分(PI)控制,在速度调节环上引入一种新颖的闭环PI型迭代学习控制(ILC)算法。通过ILC算法不断学习调节电机实际转速与给定转速的差值,达到对电机q轴给定电流的在线补偿,从而抑制电机运行时的周期性转速脉动,同时可提高转速跟踪精度。结果表明,引入ILC算法后,电机转速转矩脉动均得到了有效削弱,转速跟踪精度也得到了大大的提高。

Permanent magnet synchronous motor（PMSM） is widely used in industrial control field, but it is still diffi- cult to be applied to high precision motion control field because of the large torque ripple of PMSM.Considering the stability of the mechanical speed sensor and the system cost, the model reference adaptive system （MRAS） control is used to estimate the motor speed.Based on the PMSM vector control MRAS,combined with the traditional proportional integral （PI） control, a novel closed-loop PI type iterafive learning control （ILC） algorithm is introduced on the veloci- ty adjustment loop.By ILC algorithm continuously leam to adjust the difference between the actual motor speed and the given speed, compensating the motor q axis of a given current online, thus inhibiting the motor running cycle speed pulsation and improving the speed tracking accuracy.The results show that the pulse speed of the motor is ef- fectively weakened after ILC algorithm is introduced, and the speed tracking accuracy is greatly improved.