Research of parameter setting method of ADRC for PMSM servo system based on RBFNN

Abstract

About parameter setting, this paper introduces a method of Active Disturbance Rejection Control (ADRC) for Permanent Magnet Synchronous Motor (PMSM) servo system based on Radial Basis Function Neural Network (RBFNN). The parameters of Nonlinear State Error Feedback Control Law (NLSEF) and Nonlinear Extended State Observer (NLESO) in ADRC are adjusted by RBFNN, which solves the difficulty of parameter setting caused by the introduction of the nonlinear structure itself in the traditional ADRC. The validity of the parameter setting method of nonlinear ADRC is verified in simulation with the external disturbances. The response speed, Steady-state accuracy and anti-disturbance ability of the second-order ADRC are improved for a PMSM servo tracking system.