Speed estimation for an induction motor using the extended Kalman filter

This article describes the Discretized Extended Kalman Filter for speed estimation of a squirrel-cage induction motor. The filter is an observer for linear and non-linear systems and is based on the stochastic intromission, in others words, noise. There is a mathematical basis that yields excellent simulation and real-time results. It shows that the filter is an excellent estimator for measurements and non-measurement states because in addition to the speed estimation we could estimate other variables like the magnetic flux. There are simulation results with Direct Torque Control where the speed accuracy is one of the most important characteristics of filtering. The tune-up is one milestone to obtain the estimation and several rules are proposed. Finally, this paper suggests the online estimation to ensure that the motor is fully represented.