引入ESO的永磁超环面电机无模型预测电流控制

Model-free predictive current control for permanent magnet toroidal motor with extended state observer

为改善无差拍预测电流控制(DPCC)对永磁超环面电机系统参数的依赖性,研究了引入扩张状态观测器(ESO)的永磁超环面电机无模型预测电流控制(MFPCC-ESO)策略。根据永磁超环面电机的复合转子结构,引入自转运动影响系数与磁势系数,在旋转坐标系下建立该电机的时变数学模型;利用永磁超环面电机系统的输入与输出,建立该电机具有时变比例因子的超局部模型,同时引入ESO对超局部模型的干扰部分进行实时估计,并利用朱利稳定判据证明了ESO的稳定性;结合延时补偿的DPCC预测得到参考电压矢量,从而实现永磁超环面电机的MFPCC-ESO策略。对参数匹配和失配下永磁超环面电机MFPCC-ESO策略与DPCC策略进行对比分析,仿真结果表明:MFPCC-ESO策略下的永磁超环面电机具有优越的动态和稳态性能及强鲁棒性,同时该控制策略还能有效降低永磁超环面电机的输出波动。

The model-free predictive current control method for the toroidal motor with extended state observer(MFPCC-ESO)was investigated in order to reduce the dependence of deadbeat predictive current control(DPCC)on the parameters of a permanent magnet toroidal motor system.According to the composite rotor structure of a toroidal motor,the rotation motion influence coefficient and magnetomotive force coefficient were introduced.The rotating coordinate system was used to build the time-varying mathematical model of the toroidal motor.Then the ultra-local model with a time-varying scaling factor was established by using the input and output of the toroidal motor system.Meanwhile,ESO was introduced to estimate the interference part of the ultra-local model in real time,and the stability of ESO was proved by using the Jury criterion.Combining with the delay compensation DPCC,the reference voltage vector was obtained.The MFPCC-ESO for the toroidal motor was further realized.The MFPCC-ESO strategy and DPCC strategy were compared and analyzed for toroidal motor under parameter matching and mismatch.The simulation results show that the toroidal motor with the MFPCC-ESO strategy has superior dynamic performance,steady-state performance,and strong robustness.Meanwhile,the proposed control strategy can also reduce the output fluctuation of the toroidal motor effectively.