DocumentCode :
3190361
Title :
Optimization of Single-phase Induction Motor Design using Radial Basis Function Network
Author :
Bhuvaneswari, R. ; Subramanian, S.
Author_Institution :
Department of Electrical Engineering, Annamalai University, Tamilnadu, India-608002. Email: boonisridhar@rediffmail.com
fYear :
2005
fDate :
11-13 Dec. 2005
Firstpage :
35
Lastpage :
40
Abstract :
This paper presents a radial basis function (RBF) model for optimal design of single-phase induction motor. The RBF network is a new generation of artificial neural network (ANN) of auto configuring nature and extremely fast training procedure. The induction motor design optimization is formulated as a nonlinear programming problem and Simulated Annealing (SA) is used for arriving at the optimal design. RBF network is trained with this optimal data. The model so developed is applied to two test motors and the results are compared with those obtained from SA, GA and conventional method. Test results reveal that the proposed scheme determines the optimal geometry of induction motor efficiently, accurately and quickly.
Keywords :
Design optimization; genetic algorithm; radial basis function network; simulated annealing; single-phase induction motor; Artificial neural networks; Constraint optimization; Design optimization; Genetic algorithms; Induction motors; Optimization methods; Radial basis function networks; Search methods; Simulated annealing; Testing; Design optimization; genetic algorithm; radial basis function network; simulated annealing; single-phase induction motor;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
INDICON, 2005 Annual IEEE
Print_ISBN :
0-7803-9503-4
Type :
conf
DOI :
10.1109/INDCON.2005.1590119
Filename :
1590119
Link To Document :
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