中文摘要：

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.

英文摘要：

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.