基于参数在线辨识的高速永磁电机无差拍电流预测控制

During the high-speed operation of sensorless surface-mounted permanent magnet synchronous motor (SPMSM), the perturbation of electrical parameters affects the performance of current loop and the accuracy of rotor position estimation. Therefore, a deadbeat predictive current control (DPCC) method for sensorless high speed permanent magnet motor based on parameter identification was proposed. Firstly, combined with the characteristics of permanent magnet motor control system, DPCC was adopted to improve the dynamic performance of the current loop controller. Besides, the parameter sensitivity of DPCC was analyzed. Secondly, in order to solve the rank deficient problem, a total least square (TLS) method based on neuron iterative solution was used to identify the inductance, resistance and permanent magnet flux linkage on-line and step by step. Finally, the identification results were used to update the parameters of deadbeat predictive current controller and sliding mode observer. The experimental results show that DPCC method of sensorless high-speed permanent magnet motor based on parameter identification can effectively improve the steady state performance of current loop controller and the accuracy of rotor position estimation.