Chained extended Kalman filter based on FOC in speed sensorless control

High performance speed sensorless control of induction motors (IMs) calls for estimation and control schemes that offer solutions to parameter uncertainties, as well as difficulties involved with accurate flux and speed estimation. In this study, a new EKF based on estimation technique is proposed for the both problems and applied in combination with field oriented control (FOC). The chained extended Kalman filter (CEKF) includes dual EKF, differently from the other approaches in the past studies, which works in serial ways and updates each other’s model in real time. Thus applied, CEKF provides an accurate estimation of an increased number of parameters than would be possible with a single EKF, but reduces calculation complexity more greatly than tradition dual EKF algorithm. The CEKF based estimation technique performs the on-line estimations of rotor resistance, mutual inductance, rotor flux and speed, both in the transient and steady state. The effectiveness of the proposed EKF is shown by means of simulation in Matlab /Simulink environment. © 2015 ICPE Electra Publishing House . All rights reserved.