Torque Ripple Minimization of PMSM Based on Robust ILC Via Adaptive Sliding Mode Control

Torque ripples due to cogging torque, current measurement errors, and flux harmonics restrict the application of the permanent magnet synchronous motor (PMSM) that has a high-precision requirement. The torque pulsation varies periodically along with the rotor position, and it results in speed ripples, which further degrade the performance of the PMSM servo system. Iterative learning control (ILC), in parallel with the classical proportional integral (PI) controller (i.e., PI-ILC), is a conventional method to suppress the torque ripples. However, it is sensitive to the system uncertainties and external disturbances, i.e., it is paralyzed to nonperiodic disturbances. Therefore, this paper proposes a robust ILC scheme achieved by an adaptive sliding mode control (SMC) technique to further reduce the torque ripples and improve the antidisturbance ability of the servo system. ILC is employed to reduce the periodic torque ripples and the SMC is used to guarantee fast response and strong robustness. An adaptive algorithm is utilized to estimate the system lumped disturbances, including parameter variations and external disturbances. The estimated value is utilized to compensate the robust ILC speed controller in order to eliminate the effects of the disturbance, and it can suppress the sliding mode chattering phenomenon simultaneously. Experiments were carried out on a digital signal processor-field programmable gate array based platform. The obtained experimental results demonstrate that the robust ILC scheme has an improved performance with minimized torque ripples and it exhibits a satisfactory antidisturbance performance compared to the PI-ILC method.