Control of Sensorless PMSM using State Dependent Model Reference Adaptive System and Adaptive Augmented Observer

Permanent magnet synchronous motors due to its high efficiency and power density, reliable performance and simple construction, industrially used. One of the problems with these Motor need accurate information to control its speed and position. Recently, because of the difficulties of the speed sensors, speed estimation is used instead of measuring it. In this paper, the state dependent model reference adaptive controller based on pseudo linearization is used to control the permanent magnet synchronous motor that its parameters are determined based on Lyapunov theory. This controller show good results by production control law, despite changing circumstances and maintain system stability despite external disturbances. Also due to uncertainty in the estimation of the position and speed of motor parameters, high impact, online identification of these parameters is necessary. In this paper, adaptive augmented observer is used to estimate speed and identify motor parameters online. The main advantage of this estimator is that speed and load torque estimation and identification of parameters are simultaneously thus volume and time calculations are reduced. The simulation results show convenient tracking of desired speed with the load torque, changing the motor parameters and the speed reference.