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
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;
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
DOI :
10.1109/WCICA.2002.1020830
