PMSM Torque Ripple Minimization Using an Adaptive Iterative Learning Control

Parasitic torque pulsations existing in permanent magnet synchronous motors (PMSMs) degrade their performance, particularly at low speeds. In this paper, an adaptive iterative learning control (ILC) strategy is proposed for torque ripple minimization in a PMSM drive system. An analysis is conducted to study the impact of ILC gains on the steady-state and transient performance of the system. Accordingly, a real-time tuning method based on multi-variable sliding-mode extremum seeking (MSES) is proposed to adjust the ILC gains. The proposed controller is applied to a PMSM and its performance is verified by comparing the results with a similar controller using a non-adaptive ILC scheme. The results demonstrate the effectiveness of the proposed ILC scheme in achieving lower torque ripples and faster transient performance.