將模糊徑向基函數(shù)(f-RBF)神經(jīng)網(wǎng)絡(luò)算法用于永磁同步電機(jī)(PMSM)的速度控制。針對
電機(jī)的動(dòng)態(tài)和非線性特點(diǎn)，結(jié)合PMSM驅(qū)動(dòng)的矢量控制方法, 設(shè)計(jì)了f-RBF在線辨識(shí)器和速度控制器。在Matlab/Simulink下將該方法與傳統(tǒng)的PID控制PMSM進(jìn)行了仿真比較。實(shí)驗(yàn)結(jié)果表明了該方法的有效性，且系統(tǒng)響應(yīng)速度快，動(dòng)態(tài)性能優(yōu)異, 魯棒性好。
關(guān)鍵詞：永磁同步電機(jī)，自適應(yīng)控制，模糊徑向基函數(shù)神經(jīng)網(wǎng)絡(luò)，在線系統(tǒng)辨識(shí)
Radius Basis Function Neural Network Based Vector Control of PMSM (Haiqiong Liu) Abstract: This paper presents an approach of speed control for Permanent Magnet Synchronous Motor (PMSM) using fuzzy Radius Basis Function (f-RBF) neural network. Based on motor dynamics and non-linear load characteristics, a f-RBF on-line identifier and speed controller is developed and integrated with the vector control scheme of the PMSM drive. Simulation and comparison between this approach and traditional PID control to PMSM is taken under Matlab/Simulink. With the presented method, satisfactory response speed and precision as well as good dynamic performance and strong robustness were obtained by experiments.
Key words: PMSM, adaptive control, fuzzy radial basis function neural network, On-line SystemI dentification,