Speed control of sensorless induction motor drive based on model predictive control

In this paper, the model predictive control (MPC) technique for controlling the speed of sensorless induction motor drive is presented. To decrease the cost and increase the reliability and affectivity of the motor drive, a full order observer for speed estimation based on the model reference adaptive system MRAS is used to estimate the rotor speed. The adaptive full-order observer based on IM equation is used to estimate stator currents and rotor flux. Lyapunov's stability criterion is employed to estimate rotor speed based on the error between the actual and estimated currents. The same algorithm deduced from Lyapunov's stability criterion is given to estimate the stator resistance, which results in the speed estimation error. A simple model of induction motor is employed in the MPC structure so as to minimize the computational load. The MPC controller design is taken into account the effect of uncertainty due to motor parameters variation and load disturbance could be reduced. The effectiveness of the proposed scheme has been successfully verified through simulations. The results proved that the induction motor with the MPC speed controller has superior transient response, and good robustness in face of uncertainties including load disturbance. Moreover, accurate tracking performance has been achieved.