学术
摘 要:
无刷双馈电机（BDFM）兼有笼型、绕线型感应电机和电励磁同步电机的共同优点，在电气传动和风力发电中具有很好的应用前景．由于无刷双馈电机两套绕组形成的复杂空间耦合关系，使得基于模型的控制方法异常复杂，为此设计了一种PID神经网络（PIDNN）的无刷双馈电机的控制方法，经过训练的PID神经网络控制器能够实现准确的转速跟踪，且有较好的动态特性，仿真结果验证了这种控制方法的有效性．[著者文摘]
文章出处:
《控制理论与应用》-2008年25卷1期 -53-56页
栏目信息:
分 类 号:
文献标识码:
A
文章编号:
1000-8152（2008）01-0053-04
PID neural network control of brushless doubly-fed machine
GUO Hong-xia, YANG Jin-ming, LIU Wen-gang （Electric Power College, South China University of Technology, Guangzhou Guangdong 510640, China）
Abstract:
Brushless doubly-fed machine （BFDM） possesses the common advantages of squirrel-cage induction machine, wire wound induction machine and electromagenetic synchoronous machine. Therefore, it has a good prospect for application in AC drive and wind generating. Because of the complicated spatial coupling characteristics of BFDM between the two windings, the control methods based on the model of BFDM are very complicated. A PID neural network controller （PIDNN） is designed and applied to the speed regulation of BFDM. The exact speed-tracking is then realized by PIDNN controller after training. The dynamics is satisfactory. Finally, the simulaiton result validates the feasibility and effectiveness of this method.[著者文摘]
Key words:
brushless doubly-fed machine; PID neural network control; speed control
基金资助:
国家自然科学基金重点资助项目（60534040）.
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