DocumentCode
2938604
Title
Research of Switched Reluctance Generator Position Sensorless Based on ANFIS by Using Finite Element Analysis
Author
Yi Ling-Zhi ; Peng Han mei ; Liu Xiang ; Wang Gen ping
Author_Institution
Coll. of Inf. Eng., Xiangtan Univ., Xiangtan, China
fYear
2011
fDate
25-28 March 2011
Firstpage
1
Lastpage
4
Abstract
A new method of SRG Position Sensorless based on Self-adaptive Fuzzy Neural Network by using Finite Element Analysis is proposed in this paper. Through current and magnetic linkage to get angle of SRG rotor position, so the nonlinear mapping of current-magnetic linkage-angle can be built. By training these sample data, the angle of SRG rotor position can replaced by the output of ANFIS, to achieve SRG Position Sensorless. Simulation results show that the error of between actual rotor position and estimate rotor position is small, SRG can commutate with great accuracy, the output voltage of SRG in variable-speed directly driven wind power generation systems is essentially constant, and SRG is working well.
Keywords
finite element analysis; fuzzy neural nets; learning (artificial intelligence); power engineering computing; reluctance generators; wind power plants; ANFIS; current linkage; current-magnetic linkage-angle; finite element analysis; magnetic linkage; nonlinear mapping; rotor position; self-adaptive fuzzy neural network; switched reluctance generator position sensorless; wind power generation system; Artificial neural networks; Couplings; Finite element methods; Magnetic domains; Rotors; Training; Wind speed;
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.2011.5748973
Filename
5748973
Link To Document