The Neural Network Adaptive Control for the Nonlinear Load of the Permanant Magnet Synchronous Motor

Author

Nuo, Li ; Jiang, Wang ; Ronghua, Zhang

Author_Institution

Tianjin Univ., Tianjin

fYear

2007

Firstpage

72

Lastpage

76

Abstract

To solve the electromagnetic torque ripple caused by uncertain nonlinear factor of the Permanent Magnet Synchronous Motor (PMSM) and improve the quick response and the smooth trajectory tracking of the servo system, a robust smooth trajectory tracking method based on Neural Network compensation is designed to the servo control system in this paper. Based on the mathematical model of the PMSM and it´s nonlinear load, a Neural Network backstepping control method and two-order nonlinear smooth trajectory filter is presented in this paper. Finally, the validity and effectiveness of this control method are verified through the practical DSP experiments applied into AC servo control systems.

Keywords

adaptive control; compensation; machine control; neurocontrollers; nonlinear control systems; permanent magnet motors; position control; robust control; servomotors; synchronous motors; tracking; uncertain systems; AC servo control system; DSP experiment; electromagnetic torque ripple; mathematical model; neural network adaptive control; neural network backstepping control method; neural network compensation design; nonlinear load; permanent magnet synchronous motor; robust smooth trajectory tracking; two-order nonlinear smooth trajectory filter; uncertain nonlinear factor; Adaptive control; Backstepping; Mathematical model; Neural networks; Permanent magnet motors; Robust control; Servomechanisms; Servosystems; Synchronous motors; Trajectory; Neural Network; Servo System; Smooth Tracking Control; Torque Ripple;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference, 2007. CCC 2007. Chinese

Conference_Location

Hunan

Print_ISBN

978-7-81124-055-9

Electronic_ISBN

978-7-900719-22-5

Type

conf

DOI

10.1109/CHICC.2006.4347478

Filename

4347478