Title :
Torque ripple minimization in PM synchronous motors based on backstepping neural network
Author :
Zhang Xiangdong ; Jiang, Wang ; Huiyan, Li
Author_Institution :
Dept. of Autom., Tianjin Univ., China
Abstract :
The electromagnetic torque introduces ripples into the system due to the nonlinearity of the permanent magnetic field and the change of the stator winding, which generate speed oscillations and deteriorate the performance of PM synchronous motor (PMSM). In this paper, we have given the numerical description of the ripples and proposed backstepping Neural Network (NN) control scheme to minimize them. First, online weight-tuning based NNs compensate the torque nonlinearity and external disturbances with its approximation characteristic, and make them satisfy the linear parameter requirement of backstepping; Second, backstepping is applied based on the model of PMSM; At last, the comparison simulation with PID are added to demonstrate the effectiveness of the proposed method.
Keywords :
machine control; neurocontrollers; permanent magnet motors; synchronous motors; torque control; PID control; backstepping neural network; electromagnetic torque; online weight tuning based neural net; permanent magnet synchronous motors; permanent magnetic field nonlinearity; stator winding; torque ripple minimization; Backstepping; Control systems; Intelligent networks; Linear feedback control systems; Neural networks; Nonlinear control systems; Shape control; Stators; Synchronous motors; Torque;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1342350