將模糊徑向基函數(shù)(f-RBF)神經(jīng)網(wǎng)絡算法用于永磁同步電機(PMSM)的速度控制。針對
電機的動態(tài)和非線性特點，結合PMSM驅動的矢量控制方法, 設計了f-RBF在線辨識器和速度控制器。在Matlab/Simulink下將該方法與傳統(tǒng)的PID控制PMSM進行了仿真比較。實驗結果表明了該方法的有效性，且系統(tǒng)響應速度快，動態(tài)性能優(yōu)異, 魯棒性好。
關鍵詞：永磁同步電機，自適應控制，模糊徑向基函數(shù)神經(jīng)網(wǎng)絡，在線系統(tǒng)辨識
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,