Research on linear motors models based on the combined kernel function of multiple support vector machine

In order to solve the rapid computing problems of parameter optimization for the linear motor, a nonparametric modeling method was proposed based on the multiple output support vector machine (SVM). The SVM model of the permanent magnet synchronous linear motor was established by the kernel function combination of the high/low-order polynomial kernel function where the penalty parameter was optimized by the cross validation algorithm. The simulation and experimental results carried out on the combined kernel function and support vector machine indicate that the computational efficiency and precision of the motor model meet the large-scale computing requirements in the motor structure optimization area.