Stability improvement of induction motor based on stator parameter identification scheme

摘要

A new method for stator resistance identification based on wavelet network is presented to improve the operating performance of induction motor. The ripple of the torque is kept constant, resulting in a variable switching frequency, which depends on the tolerance band of the control. Due to wavelet transform behaving good localization property in both time and frequency space and multi-scale property, the wavelet function is adopted as the basic function of neural network. The current error and the change in the current error are the inputs of the wavelet network and the stator resistance error is the output of the wavelet network. The network parameters are initialized by the improved least squares algorithm. The parameters of wavelet network are tuned online to approximate the unknown nonlinear model with an appropriately chosen adaptive mechanism. The proposed method is proved to be efficient to reduce the torque ripple and current ripple by detailed comparison simulation results.