Iterative Learning Observer-Based Composite SOSM Control for PMSM Speed Regulation Problem With Mismatched Disturbances
Chang Cheng, Lu Liu, Shihong Ding
Abstract
Aiming at the speed regulation problem of the permanent magnet synchronous motor (PMSM) in the presence of torque ripple and external disturbance, a composite control algorithm is proposed by combining an iterative learning control based on disturbance observer (ILC-DOB) with a second-order sliding mode (SOSM) control scheme, which can improve the robustness and the ability of torque ripple suppression for the PMSM speed regulation system. Firstly, the mathematical model of the PMSM is constructed and then transformed into a SOSM dynamics with mismatched disturbance. Secondly, a novel ILC-DOB is introduced to estimate the mismatched disturbance containing periodic torque ripple. Finally, a composite SOSM control algorithm with state feedback and feedforward compensation is constructed. Consequently, the robustness of the PMSM system is improved, and the torque ripple is also minimized. On this basis, the performance of the PMSM speed regulation system is improved. Through experimental results, the effectiveness of the proposed composite control algorithm is verified.