Simultaneous identification of the linear and nonlinear characteristics of motor drives using Dynamic Wavelet Networks

This paper presents a novel Dynamic Wavelet Network (DWN) structure to accurately model and identify a nonlinear motor drive system. The proposed approach uses an adaptive learning algorithm to identify simultaneously the linear parameters and friction nonlinearity of the drive system from the time response data. A DC motor drive system is used as a case study to validate the identification methodology.