Compressed Extended Kalman Filter for Sensorless Control of Asynchronous Motor
The sensorless control applications of Induction Motors (IM) are largely expanding in industrial applications. This paper presents a new and effective sensorless control approach for IM drive based on Compressed Extended Kalman Filter (CEKF). Moreover, the estimations of the rotor flux components and the IM motor speed are implemented through CEKF algorithm. The effectiveness of the proposed control system of IM and estimation algorithm has been verified through simulation work using MATLAB/Simulink at different torque loads. Furthermore, the estimation scheme has been experimentally tested at full load. The comparison between the Extended Kalman Filter (EKF) and the CEKF are carried out and satisfying simulation and experimental results have shown that the CEKF algorithm is very effective in estimating the IM states with lower computational costs, low storage memory and less complexity during implementation compared to the EKF. The sensorless control system has demonstrated good performance at different torque loads conditions.
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