DocumentCode :
2940719
Title :
Artificial Neural Network-Based Controller for Permanent Magnet Synchronous Motor Servo System
Author :
Qu, Xiaoguang ; Han, Taidong ; Cao, Yang
Author_Institution :
Sch. of Autom., Shenyang Aerosp. Univ., Shenyang, China
fYear :
2011
fDate :
25-28 March 2011
Firstpage :
1
Lastpage :
4
Abstract :
This paper implement an online training of dynamic neural networks (NNs) for identification and control of permanent magnet synchronous motor (PMSM) servo system. Utilizing two multilayer feed-forward NNs, it makes no such assumptions. The two networks work in tandem to simultaneously achieve system identification and adaptive control. The proposed control system is designed and its effectiveness in tracking application is verified by simulations. The ability of the controller to achieve the tracking process with a high degree of accuracy, even in the presence of external disturbance is also demonstrated. The simulation results clearly demonstrate the success of the proposed control structure.
Keywords :
adaptive control; control system synthesis; feedforward neural nets; machine control; neurocontrollers; permanent magnet motors; servomotors; synchronous motors; adaptive control; artificial neural network-based controller; feed-forward NN; permanent magnet synchronous motor servo system; tracking process; Adaptation model; Artificial neural networks; Induction motors; Neurons; Rotors; Servomotors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2011 Asia-Pacific
Conference_Location :
Wuhan
ISSN :
2157-4839
Print_ISBN :
978-1-4244-6253-7
Type :
conf
DOI :
10.1109/APPEEC.2011.5749083
Filename :
5749083
Link To Document :
بازگشت