Fuzzy Radius Basis Function Neural Network Based Vector Control of Permanent Magnet Synchronous Motor

被引：1
|
作者：
Gu, Zhihe [1 ]
Li, Hui [2 ]
Sun, Yongkui [3 ]
Chen, Yong [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Mechatron Engn, Chengdu 610054, Sichuan, Peoples R China
[2] Univ Elect Sci & Technol China, Inst Aeronaut & Astronaut, Chengdu 610054, Peoples R China
[3] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu 610054, Peoples R China
来源：
2008 INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION: (ICMA), VOLS 1 AND 2 | 2008年
关键词：
D O I：
10.1109/ICMA.2008.4798756
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The Permanent Magnet Synchronous Motor (PMSM) is a dynamic, multi-variable and non-linear system, and the conventional PID control method is very difficult to meet the requirement for high accuracy control. This paper presents an approach of control for PMSM servo system using fuzzy Radius Basis Function (f-RBF) neural network which has the advantages of strong adaptive ability and nonlinear approximation capability Combined with vector control scheme, the f-RBF neural network based online identifier and controller is constructed to identify and control system. Simulation and comparison between this approach and conventional 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.
引用
收藏
页码：224 / +
页数：2
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