Induction motor control in the low-speed range using EKF- and LKF-based algorithms

This paper deals with the rotor speed detection in induction motor drives when very low-speed operation and high performances are required. The application of two Kalman filter-based algorithms to estimate the rotor flux components, rotor speed and position, and equivalent disturbance is proposed. The extended Kalman filter-based algorithm is used to obtain a correct implementation of direct vector control, since it estimates the rotor flux components. The linear Kalman filter-based algorithm estimates: the equivalent disturbance, that is compensated by the injection of a feedforward signal, the rotor speed, which is good enough to be used as feedback signal in high-dynamics vector control, and the rotor position, which could be used for position control. The effects of the variations of both mechanical and electrical parameters are considered, to verify the robustness of the proposed control scheme