基于改进滑模观测器的双定子电动机控制系统研究

Research on Control System of DS-PMBL Motor Based on Improved Sliding Modes Observer

为了提高双定子永磁无刷(DS-PMBL)电动机控制系统的稳定性,在基于滑模观测器(SMO)的控制方法基础上,提出了一种改进的SMO,并设计了卡尔曼滤波器与低通滤波器(LPF)形成级联的两级滤波方法。SMO可以通过测量DS-PMBL的电压、电流来获得转子位置和转速信息,但是观测反电势中存在的高频噪声和纹波会直接影响到估测精度。采用饱和函数对传统SMO进行改进,并引入变截止频率的LPF与卡尔曼滤波器对反电势再次滤波,最后使用锁相环计算出转子位置和转速信息,经过改进的SMO能够显著抑制扰动,并且估测信息精度得到明显提升,提高了系统的稳定性。

In order to improve the stability of DS-PMBL motor control system,based on the control method of SMO,an improved SMO is proposed.A two-level filtering method for cascading Kalman filter and LPF is designed.SMO can obtain rotor position and speed information by measuring the voltage and current of DS-PMBL,but observing high-frequency noise and ripple in the antipotential will directly affect the estimation accuracy.Therefore,the saturation function is used to improve the traditional SMO,and the LPF and Kalman filters with variable cut-off frequencies are used to filter the reverse potential again.Finally,the phase lock loop is used to calculate the rotor position and speed information.The improved SMO can significantly inhibit the disturbance.Moreover,the accuracy of information estimation is obviously improved,which improves the stability of the system.