High-Precision Repetitive Motion Control in Permanent Magnet Synchronous Motor Using a Periodic Adaptive Extended State Observer

摘要

This paper focuses on estimating and compensating the lumped disturbances in the repetitive motion control system of permanent magnet synchronous motor. A Periodic Adaptive Extended State Observer (PAESO) consisting of a normal Extended State Observer (ESO) and a refined ESO is proposed. The normal ESO is designed to capture the approximate range of the disturbances, and the refined ESO is developed to optimize the quantity of the estimated lumped disturbances by integrating real-time position tracking error. Based on PAESO, a hybrid controller, including a feedback branch and a feedforward branch, is presented to make the overall system stable and the position tracking error convergent towards zero. The effectiveness of the proposed PAESO is verified through three real-time experiments. Experimental results show that a high-precision tracking performance is obtained by the proposed PAESO.