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基于RBF神经网络空间矢量法对PMSM的控制
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2009-06-01
王尚岱
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将模糊径向基函数(f-RBF)神经网络算法用于永磁同步电机(PMSM)的速度控制。针对
电机的动态和非线性特点，结合PMSM驱动的矢量控制方法, 设计了f-RBF在线辨识器和速度控制器。在Matlab/Simulink下将该方法与传统的PID控制PMSM进行了仿真比较。实验结果表明了该方法的有效性，且系统响应速度快，动态性能优异, 鲁棒性好。
关键词：永磁同步电机，自适应控制，模糊径向基函数神经网络，在线系统辨识
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,
电机的动态和非线性特点，结合PMSM驱动的矢量控制方法, 设计了f-RBF在线辨识器和速度控制器。在Matlab/Simulink下将该方法与传统的PID控制PMSM进行了仿真比较。实验结果表明了该方法的有效性，且系统响应速度快，动态性能优异, 鲁棒性好。
关键词：永磁同步电机，自适应控制，模糊径向基函数神经网络，在线系统辨识
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,
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