The optimization of EKF algorithm based on current errors for speed-sensorless control of induction motors

In this study, an optimized extended Kalman filter (EKF) is designed in order to achieve high performance speed-sensorless control of induction motors (IMs). The EKF algorithm estimates the stationary axis components of rotor fluxes, φ
_rα
and φ
_rβ
, the rotor angular velocity, ω
_m
, the rotor resistance, R'
_r
, besides the stationary axis components of stator currents, i
_sα
and i
_sβ
, which are measured as output as well. Also, an optimization process is performed using errors between measured and estimated current components to obtain satisfying estimation performance with EKF. The experimental results prove the high performance control of the proposed system.