基于自适应迭代优化FSMO的PMSM无感控制

Sensorless Control of Permanent Magnet Synchronous Motor Based on AIFSMO

针对磁链滑模观测器(flux sliding mode observer,FSMO)中存在的抖振以及转子位置估计精度的问题,提出了一种自适应迭代磁链滑模观测器(adaptive iterative flux sliding mode observer,AIFSMO)。首先,构建了以电流和磁链为状态变量的FSMO模型;其次,为了减少计算FSMO最优增益的迭代次数,构建了带有速度和电流的误差准则函数对其进行自适应调整,减少了系统的抖振;最后,与转子速度自适应辨识相结合,设计了改进转子位置估计器,在稳态、转速突变和负载突变3种工况下进行仿真测试。测试结果表明,与基于PLL(phase locked loop,PLL)的FSMO相比,消除了系统的抖振,提高了转子速度和位置的估计精度,在转速和负载突变时使系统的动态性能得到加强,减小了相位延迟。

In order to reduce the chattering of flux sliding mode observer(FSMO)and improve the estimation accuracy of rotor position,an adaptive iterative flux sliding mode observer(AIFSMO)is proposed.Firstly,the FSMO model with current and flux as state variables is constructed;Secondly,in order to reduce the number of iterations to calculate the optimal gain of FSMO,an error criterion function with speed and current is constructed to adjust it adaptively to reduce the chattering of the system;Finally,an improved rotor position estimator is designed in combination with rotor speed adaptive discrimination.In this paper,simulations are conducted under three operating conditions:steady state,sudden speed change and sudden load change.The results show that compared with the PLL(phase locked loop,PLL)based FSMO,this paper eliminates the jitter of the system,improves the accuracy of rotor speed and position estimation,enhances the dynamic performance of the system during the sudden speed and load changes,and reduces the phase delay.