DocumentCode
2001804
Title
The third-order induction motor parameter estimation using an adaptive genetic algorithm
Author
Zhou, Xiaoyao ; Cheng, Haozhong ; Ju, Ping
Author_Institution
Dept. of Electr. Eng., Shanghai Jiao Tong Univ., China
Volume
2
fYear
2002
fDate
2002
Firstpage
1480
Abstract
Presents an adaptive genetic algorithm for third-order induction motor model parameter estimation. The crossover and mutation probability of the adaptive genetic algorithm change according to the fitness statistics of the population at each generation. The proposed algorithm can enhance the convergence performance of the genetic algorithm and prevent a premature problem. This algorithm is successfully applied to the third-order induction motor model parameter estimation.
Keywords
electric machine analysis computing; genetic algorithms; induction motors; parameter estimation; adaptive genetic algorithm; convergence performance; crossover; mutation probability; third-order induction motor parameter estimation; Biological cells; Genetic algorithms; Induction motors; Parameter estimation; Power system modeling; Power system transients; Rotors; Stators; Testing; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN
0-7803-7268-9
Type
conf
DOI
10.1109/WCICA.2002.1020830
Filename
1020830
Link To Document