Recursive Wavelet Elman neural network for a synchronous reluctance motor

This paper proposed recursive Wavelet Elman neural network (RWENN) speed control for synchronous reluctance motor (SynRM). Wavelet neural network (WNN) activation function is replaced by wavelet functions which WNN combines wavelet transform with time domain, analytical capabilities and scale neural network. This paper proposed RWENN that has satisfactory control nonlinear problem in SynRM. We used the discrete Lyapunov theory to ensure network converges. Finally, the experimental results validated RWENN has satisfactory performance in SynRM.