Sensorless Control of Induction Motor with Extended Kalman Filter on TMS320F2812 Processor

This paper describes discretized Extended Kalman Filter (EKF) for speed estimation of squirrel cage induction motor. Speed and rotor fluxes are estimated from the measured terminal voltages and currents without anymore additional filter. There is a mathematical basis that yields excellent simulation and real time results. In this, speed is considered as a parameter and state. The speed of an induction motor is estimated by MATLAB simulation under low speed regions and it is verified using TMS320F2812 DSP Code Composer Studio. Estimated values along with other measured states are used for closed loop control. The current control is performed under synchronously rotating reference frame and the estimated speed information is used for the reference frame transformation of the current controller. At low speeds, where noise is predominant, performance is improved due to the filtering action of the EKF.