带参数辨识的自适应二阶滑模观测器PMSM无传感器矢量控制

针对表贴式永磁同步电机无位置传感器矢量控制系统, 提出一种具有电机参数在线辨识的基于Super-twisting algorithm的自适应二阶滑模观测器.在两相静止坐标系下,将模型参考自适应方法与基于Super-twisting algorithm的二阶滑模方法相结合,实现反电动势的准确估计.采用李亚普诺夫理论证明观测器的稳定性,并由李亚普诺夫稳定性方程推导定子电阻和转子转速的自适应律.在同步旋转坐标系下,采用二阶滑模观测器估计永磁磁链,并将其输入位置跟踪观测器估计转子位置.该算法充分抑制了滑模抖振,同时避免了低通滤波和相位补偿环节的使用,转子位置检测不受定子电阻和永磁磁链变化的影响,具有较强的鲁棒性.仿真结果验证了所提出算法的有效性.

Adaptive second-order sliding mode observer with parameter identification for PMSM sensorless vector control

Aiming at the position sensorless vector control system of surfac permanent magnet synchronous motors, an adaptive second-order sliding mode observer with online identification of motor parameters based on a super-twisting algorithm is presented. In the two-phase stationary coordinate system, the paper combines a model reference adaptive system with a second-order sliding mode based on the super-twisting algorithm. Thus the exact estimate of the back electromotive force (EMF) is achieved. The Lyapunov theory is used to prove the stability of the observer, and the adaptive law of stator resistance and rotor speed is deduced from the Lyapunov stability equation. In the synchronous rotating coordinate system, the second-order sliding mode observer is used to estimate the permanent magnet flux. Subsequently, the identified parameter is brought in the position tracking observer to estimate the rotor position. The algorithm can effectively suppress the sliding mode chattering without the use of low-pass filter and phase compensation. The rotor position measurement is not affected by the changes of stator resistance and permanent magnet flux, which owns strong robustness. The simulation results show the effectiveness of the proposed algorithm.