Real-time discrete neural identifier for a linear induction motor using a dSPACE DS1104 board

Abstract

This paper presents a real-time discrete nonlinear neural identifier for a Linear Induction Motor (LIM). This identifier is based on a discrete-time recurrent high order neural network (RHONN) trained on-line with an extended Kalman filter (EKF)-based algorithm. A reduced order observer is used to estimate the secondary fluxes. The real-time implementation of the neural identifier is implemented by using dSPACE DS1104 controller board on MATLAB/Simulink with dSPACE RTI library and its performance is shown by graphs.