A Robust Sensorless Direct Torque Control of Induction Motor Based on MRAS and Extended Kalman Filter

In this paper, the classical Direct Torque Control (DTC) of Induction Motor (IM) using an open loop pure integration suffers from the well-known problems of integration especially in the low speed operation range is detailed. To tackle this problem, the IM variables and parameters estimation is performed using a recursive non-linear observer known as EKF. This observer is used to estimate the stator currents, the rotor flux linkages, the rotor speed and the stator resistance. The main drawback of the EKF in this case is that the load dynamics has to be known which is not usually possible. Therefore, a new method based on the Model Reference Adaptive System (MRAS) is used to estimate the rotor speed. The two different nonlinear observers applied to sensorless DTC of IM, are discussed and compared to each other. The rotor speed estimation in DTC technique is affected by parameter variations especially the stator resistance due to temperature particularly at low speeds. Therefore, it is necessary to compensate this parameter variation in sensorless induction motor drives using an online adaptation of the control algorithm by the estimated stator resistance. A simulation work leads to the selected results to support the study findings.