DocumentCode
3561722
Title
The induction motor parameter estimation through an adaptive genetic algorithm
Author
Xiaoyao Zhou ; Haozhong Cheng
Author_Institution
Dept. of Electr. Eng., Shanghai Jiao Tong Univ., China
Volume
1
fYear
2004
Firstpage
494
Abstract
This paper presents a new adaptive genetic algorithm for third-order induction motor model parameter estimation. The crossover and mutation probability of adaptive genetic algorithm change according to the fitness statistics of the population at each generation. The proposed algorithm can enhance the convergence performance of GA and prevent premature problems. This algorithm is successfully applied to the third-order induction motor model parameter estimation.
Keywords
adaptive estimation; convergence of numerical methods; genetic algorithms; induction motors; load (electric); parameter estimation; power system analysis computing; probability; GA; adaptive genetic algorithm; convergence performance; crossover; fitness statistics; induction motor; mutation probability; third-order model 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
Universities Power Engineering Conference, 2004. UPEC 2004. 39th International
Print_ISBN
1-86043-365-0
Type
conf
Filename
1492053
Link To Document