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作 者:杨帆[1] 赵希梅[1] 金鸿雁 王晓东[1] YANG Fan;ZHAO Ximei;JIN Hongyan;WANG Xiaodong(School of Electrical Engineering,Shenyang University of Technology,Shenyang 110870,Liaoning Province,China)
机构地区:[1]沈阳工业大学电气工程学院,辽宁省沈阳市110870
出 处:《中国电机工程学报》2023年第22期8935-8943,共9页Proceedings of the CSEE
基 金:辽宁省自然科学基金计划重点项目(20220540876)。
摘 要:当永磁同步电机(permanent magnet synchronous motor,PMSM)采用有限集模型预测控制(finite control set model predictive control,FCS-MPC)时,性能易受PMSM参数变化的影响,PMSM与控制器之间的参数不匹配会严重影响预测控制的性能。因此,该文提出一种基于无参数PMSM的自适应FCS-MPC控制策略,能够准确地实现预测控制而无需了解电机参数。针对PMSM多参数在线辨识时存在的欠秩问题,利用FCS-MPC固有的开关纹波能产生持续激励的特性,采用递推最小二乘法(recursive least squares,RLS)实现多参数辨识。此外,针对采用FCS-MPC时的逆变器死区时间补偿问题,提出一种考虑死区时间矢量的合成电压矢量输出方案,进一步提高预测控制性能。最后,通过实验验证了所提方法的有效性,实验结果表明,与基于模型的常规FCS-MPC解决方案相比,所提方法能减小预测误差,并且对参数变化和模型不确定性具有非常强的鲁棒性。When using finite control set model predictive control(FCS-MPC)for permanent magnet synchronous motor(PMSM),the performance is easily influenced by the change of PMSM parameters.Parameter-mismatch between PMSM and controller will seriously reduce the performance of predictive control.Therefore,this paper proposed a parameter-free adaptive predictive control method,which could accurately accomplish predictive control without knowing the motor parameters.To address the rank-deficient problem of PMSM multi-parameter online identification,this paper exploites the inherent switching ripple of FCS-MPC to generate persistent excitation,and uses the recursive least squares(RLS)algorithm to achieve multi-parameter identification.In addition,the compensation of inverter dead-time is considered,and a synthetic voltage vector output considering dead-time vector is proposed to improve the predictive control performance.Finally,the effectiveness of the method is verified by experiments,and the results show that the proposed method can reduce the prediction error and is robust to parameter variations or model uncertainties compared to the model-based conventional FCS-MPC.
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