On-line parameter identification and self-tuning PI controller for permanent magnet synchronous motor.

The motion performance of the robot largely depends on the PMSM control performance for the electrically driven robot. During the long-term operation of the robot, the motor temperature will rise. At this time, the motor resistance and flux linkage will change with the increase of temperature. When the robot runs, the working current of the motor increases sharply, and the flux linkage and inductance of the motor will be affected by magnetic circuit saturation. The change of motor parameters lead the motor control system performance to be worse. It is necessary to identify the motor parameters on-line to achieve high-performance control in the process of robot motion. A method based on a combination of forgetting factor recursive least squares algorithm (FFRLS) and model reference adaptive system (MRAS) is proposed in this paper, which can accurately identify the motor parameters of robot on-line, and improve the identification speed. The PI controller parameters of the motor's current loop are self-tuning on-line to realize the high-performance based on the identification values of the motor resistance and inductance.