Model Predictive Direct Torque Control of Induction Motor Based on Online Parameter Identification

The model predictive direct torque control of AC induction motor is a promising high-performance motor control algorithm, but it depends heavily on the accuracy of motor parameters. In order to solve this problem, an online parameter identification scheme based on model reference adaptive system and sliding mode observer is proposed to identify both stator and rotor resistance. The rotor resistance is identified by using a reactive-power-based model reference adaptive system, and the observed value of the rotor flux is obtained at the same time. The stator resistance can be identified by the sliding mode observer from the obtained rotor flux and rotor resistance. According to the Popov’s superstability theory, the stability of system is proved. The validity of the proposed method is verified by simulation.