摘要
介绍了利用小波神经网络进行开关磁阻电机建模的整个过程,包括静态磁链特性曲线簇的获取、静态矩角特性的测量、利用小波神经网络实现磁链,角度和电流的非线性映射关系,以及用小波神经网络实现通过角度和电流求取转矩,然后在MATLAB/Simulink环境下搭建SRM控制系统,并将仿真运行结果进行实验验证。通过实验对比,证明了该方法的正确性。
This paper describes the process of modeling for switched reluctance motor （SRM）, based on the wavelet neural network （WNN）, including getting the static flux-linkage characteristics, measurement of the static torque characteristics, getting the nonlinear relationship between current, flux-linkage, and rotor position by means of WNN, and getting the profiles of torque by means of WNN, through current-angle then builds the SRM control system in the environment of MATLAB/Simulink. By verifing the result of simulation with the experiment data, this method of modeling is proved to be right. [Ch,11 fig.9 ref.]
出处
《轻工机械》
CAS
2010年第4期91-94,共4页
Light Industry Machinery
关键词
开关磁阻电机
小波神经网络
矩角模型
磁链特性
switched reluctance motor
wavelet neural network
torque-angle model
flux-linkage characteristics
