DocumentCode :
3550070
Title :
A robust position controller design for PM synchronous motor using neural network
Author :
Jun, Wang ; Hong, Peng
Author_Institution :
Sch. of Electr. Inf., Xihua Univ., Sichuan, China
Volume :
3
fYear :
2004
fDate :
6-9 Dec. 2004
Firstpage :
2134
Abstract :
A robust position controller for permanent magnet synchronous motor is described in this paper. First, linear quadratic method is employed to design the permanent magnet synchronous motor system approximately linear using field orientation theory. Then, the neural network technique with adaptive learning rates is implemented to make the system insensitive to the uncertainties including parameter variations and external disturbance in the whole control process. Finally, the experimental results verify that the dynamic behaviors of the proposed control systems are robust with regards to uncertainties.
Keywords :
control system synthesis; linear quadratic control; machine control; neural nets; neurocontrollers; permanent magnet motors; position control; robust control; synchronous motors; PM synchronous motor; adaptive learning; field orientation theory; linear quadratic method; neural network; permanent magnet synchronous motor; robust position controller design; Adaptive control; Adaptive systems; Control systems; Linear approximation; Neural networks; Permanent magnet motors; Programmable control; Robust control; Synchronous motors; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Automation, Robotics and Vision Conference, 2004. ICARCV 2004 8th
Print_ISBN :
0-7803-8653-1
Type :
conf
DOI :
10.1109/ICARCV.2004.1469494
Filename :
1469494
Link To Document :
بازگشت