Position detection of BLDC rotor based on adaptive wavelet neural network  

作　　者：李永红 陈家斌 赵圣飞 岳凤英 

机构地区：[1]Beijing Institute of Technology,Beijing 100081,China [2]School of Information and Communication Engineering,North University of China,Taiyuan 030051,China

出　　处：《Journal of Measurement Science and Instrumentation》2012年第1期26-30,共5页测试科学与仪器（英文版）

基　　金：China Postdoctoral Science Foundation(No.74133)

摘　　要：Brushless DC(BLDC)motor is a complex nonlinear system,of which some parameters will also change during operation.Therefore,obtaining accurate rotor position directly through the line voltage becomes more difficult.So a new method is proposed in this paper which uses three line voltages as the input signal to identify the motor position based on adaptive wavelet neural network(WNN)and the differential evolution(DE)algorithm to optimize WNN structures,thus realizing the improvement of accuracy,exactness of the communication signals and convergence speed of the rotor position identification.Finally,both simulations and experimental results show that the proposed method has high accuracy of recognizing rotor position and strong orientation ability.Brushless DC （BLDC） motor is a complex nonlinear system, of which some parameters will also change during operation. Therefore, obtaining accurate rotor position directly through the line voltage becomes more difficult. So a new method is proposed in this paper which uses three line voltages as the input signal to identify the motor position based on ada- ptive wavelet neural network （WNN） and the differential evolution （DE） algorithm to optimize WNN structures, thus real- izing the improvement of accuracy, exactness of the communication signals and convergence speed of the rotor position identification. Finally, both simulations and experimental results show that the proposed method has high accuracy of recognizing rotor position and strong orientation ability.

关 键 词：Brushless DC(BLDC) adaptive wavelet neural network differential evolution(DE)algorithm 

分 类 号：TM33[电气工程—电机] TP183[自动化与计算机技术—控制理论与控制工程]