无轴承永磁同步电机最小二乘支持向量机非线性建模  

Nonlinear modeling of bearingless permanent magnet synchronous motors with least squares support vector machiness

作　　者：孙晓东[1,2] 朱熀秋[2] 杨泽斌[2] 张涛[2] 

机构地区：[1]江苏大学汽车工程研究院,江苏镇江212013 [2]江苏大学电气信息工程学院,江苏镇江212013

出　　处：《控制理论与应用》2012年第4期524-528,共5页Control Theory & Applications

基　　金：国家自然科学基金项目资助项目(61104016);江苏省高校自然科学研究面上基金资助项目(11KJB510002);国家"863"高技术研究发展计划资助项目(2007AA04Z213);江苏省2010年研究生科研创新计划资助项目(CX10B 270Z);江苏高校优势学科建设工程资助项目(苏政办发[2011]6号)

摘　　要：无轴承永磁同步电机的磁链特性表现为严重的非线性,常规的解析法所建立的模型难以准确反映无轴承永磁同步电机的实际特性.因此,提出利用最小二乘支持向量机建立无轴承永磁同步电机非线性模型的新方法.在介绍最小二乘支持向量机回归理论的基础上,利用有限元法得到的样本建立了无轴承永磁同步电机的最小二乘支持向量机非线性模型,并与神经网络方法进行了比较.仿真结果表明,所建模型具有较好的鲁棒性和预测精度.最后给出了应用该模型实现无轴承永磁同步电机优化控制的方法.The flux linkage characteristic of the bearingless permanent magnet synchronous motor（BPMSM） is highly nonlinear,and the conventional mathematical model established by analysis method can not reflect the real characteristics of the BPMSM.Therefore,a novel modeling method is proposed for the BPMSM to take into account its nonlinearity more accurately by using the least squares support vector machiness（LSSVM）.After the regression theory of the LSSVM is introduced,the LSSVM model of the BPMSM is built up by using the sampled data obtained from the experimental prototype with the finite elements method.Moreover,the LSSVM model is compared with the model based on neural network method.Simulation results show that the proposed model has desirable robustness and high accuracy.Finally,the optimal controller based on the modeling for the BPMSM is developed.

关 键 词：无轴承永磁同步电机 非线性模型 最小二乘支持向量机 建模 

分 类 号：TM341[电气工程—电机] TM351