Improved PMSM pulsating torque minimization with iterative learning and sliding mode observer

Abstract

In this paper, the novel concept of applying the iterative learning control (ILC) to achieve pulsating torque minimization in the PMSM is presented. Parasitic torque pulsations in the PMSM are generated due to the distortion of the stator flux linkage distribution, variable magnetic reluctance at the stator slots, and secondary phenomena such as current measurement off-set as well as scaling errors. The consequences are speed oscillations that deteriorate the performance of the drive in high-performance servo applications. The proposed torque learning controller compares the desired and instantaneously estimated motor torque and generates the reference current signal iteratively from cycle to cycle so as to reduce the pulsating torque. In order to estimate the torque ripples, a novel disturbance estimator: gain scheduled sliding mode observer is further developed to facilitate the implementation of torque learning control. The proposed control algorithm is evaluated through real-time implementation and experimental results validate the effectiveness of the proposed scheme.