Adaptation Phase-Locked Loop Speed and Neuron PI Torque Control of Permanent Magnet Synchronous Motor

Abstract

This paper presents an excellent software phase-locked loop speed control system of permanent magnet synchronous motor (PMSM). A loop-gain adaptation scheme is developed using model reference adaptive system (MRAS) theory to suppress the torque disturbance which effect on motor speed. The following three points including accurate steady-state speed, fast transient response, and insensitivity to disturbance are especially important for speed control of permanent magnet synchronous motor. The software phase-locked loop (SPLL) technique has the significant ability to obtain precise speed regulation. When the feedback signal of the motor speed is synchronized with a reference signal, perfect speed regulation can be realized. The steady-state accuracy is about 0.02%~0.1% which is difficult to be obtained by conventional proportion integral differentiation (PID) speed control. But phase-locked loop system suffers from pool dynamics and limited lock range. The gain of SPLL has great effect on the performance of system. As the loop gain becomes larger, both the maximum speed error and load increase. If the loop gain varies according to the values of phase error and speed error, the SPLL system will be adaptive between the accuracy and sensitivity to load disturbance. A model reference adaptive system is designed to confine the transient phase error within the range of [-2π 2π] at the present of torque disturbance. This means that the SPLL remains phase tracking. Also, in order to overcome the time varying and nonlinear of PMSM, and obtain the stable torque output, it is effective to utilize the neuron to seek the optimum controller parameter on line. Experiment results are presented to verify the validity of the proposed system.

Project Supported by National Natural Science Foundation of China.