Torque Ripple Minimization of Permanent Magnet Synchronous Motor Using Iterative Learning Control
Permanent Magnet Synchronous Motor (PMSM) produces the large torque ripples. It leads the system to be non-linear. Due to the presence of the airgap flux harmonics, undesirable torque pulsations occur in the motor. In this paper, Iterative Learning Control (ILC) algorithm is implemented in order to reduce the ripples that occur in the system. Iterative Learning Control is an adaptive control method which is used to reduce the ripples by repetitive learning. Most commonly used ILC schemes such as Proportional type ILC (P-ILC) and Model Predictive Control ILC (MPC-ILC) have the lower Torque Ripple Factor (TRF) and convergence. These not only reduces the torque ripples but also speed up the response of the system. The proposed algorithms are test over the permanent magnet synchronous motor and results are obtained.