Simple and robust speed sensorless vector control of induction motor using stator current based MRAC

Abstract

A novel rotor speed estimation method using model reference adaptive control (MRAC) is proposed to improve the performance of a sensorless vector controller. In MRAC methods, state variables, such as rotor flux and back EMF are estimated in a reference model and then compared with state variables estimated by using an adjustable model. The difference of these state variables is then used in an estimation of rotor speed. We propose a new MRAC method that uses the stator current as the state variable for estimating the speed. In conventional MRAC methods, the difference between state variables has the unclear relationship with the speed estimation error. But, in the proposed method, the stator current error is represented as a function of the first degree for the error value in the speed estimation. Therefore, the proposed method can produce a fast speed estimation and is robust to variations in the parameter error. In addition, the proposed method offers a considerable improvement in the performance of a sensorless vector controller at a low speed. The superiority of the proposed method is verified by simulation and experiments in a low speed region and at zero-speed.