Torque Ripple Minimization in PMSM Based on an Indirect Adaptive Robust Controller

Abstract

This paper addresses the problem of torque ripple minimization in permanent magnet synchronous motor (PMSM), which plays an important role in modern aerospace industry. Accurate motion control and disturbance compensation are challenging issues of PMSM systems, where the nonlinear disturbances are quite complicated and various uncertainties exist. To overcome these control problems, based on the adaptive robust control (ARC) algorithm, an indirect adaptive robust controller (IARC) with a robust recursive least square (RRLS) adaption law is proposed as a solution. A modified PMSM model which indicates the torque ripple generation is first derived. The IARC in current loop is then described, holding the good tracking performance of ARC algorithm and minimizing the torque ripples while speed tracking. The RRLS adaption law in IARC is synthesized based on modified model and then a correction factor is added to enhance the robustness of this adaptation law. This can enable the better parametric estimation and adaptive compensation to minimize the torque ripples. The stability of the system with the proposed controller is proved. Finally, the effectiveness of the proposed method is demonstrated by the simulation results.

Design and implementation of a novel adaptive backstepping control scheme for a PMSM with unknown load torque

“…Permanent magnet synchronous motor (PMSM) has been widely applied to alternating current servo system owing to its superior performances such as high reliability, superior power density and high efficiency [1]. Nevertheless, PMSM is a multivariable and strong coupling non‐linear control object, which is influenced by indeterminate elements such as the variation of motor parameters and external load disturbance.…”

Fixed‐Time Stability Analysis of Permanent Magnet Synchronous Motors with Novel Adaptive Control

“…It is well known that PMSM plays a very important role in the process of industrial production. Therefore, it is necessary to control chaos behavior for eliminating the undesired performance [14] which has attracted more and more consideration in the area of linear and nonlinear control [15]. The classical Lyapunov exponent methods were adopted for eliminating the chaos in PMSM [16,17].…”