基于改进支持向量机的永磁驱动器设计

Design of Permanent Magnet Drive Based on Improved Support Vector Regression

将多输出支持向量机回归方法与模糊化理论相结合,提出一种永磁驱动器的设计方法.首先,引入空间粒子群优化算法对合成核多输出支持向量回归模型参数进行寻优,在此基础上通过实验法建立了永磁驱动器的性能与结构参数的多目标回归模型;然后,运用模糊理论将多目标转化为单目标,建立了设计问题的数学模型并利用空间粒子群算法进行求解;最后,通过模型精度分析以及ANSYS仿真和样机的测试,验证了该方法的有效性.

The multi-output support vector regression with composite kernel and the fuzzy theory were applied to design permanent magnet drive. In this method, the space particle swarm optimization （SPSO） algorithm was firstly introduced to obtain the most appropriate parameter of the multi-output support vector regression with composite kernel model. In addition, through the experiment the regression model between performances and structure parameters of permanent magnet drive was established. Secondly,by using fuzzy theory,multi-objective problem was converted into single one, and the mathematical model of optimization problem was set up, which was solved by SPSO. Finally,precision analysis of model,ANSYS simulation and prototyping test were carried out, and the results verified the effectiveness of the proposed method.