DocumentCode :
2110262
Title :
Genetic algorithm for parameter identification of SACS motor testing
Author :
Dianguo, Xu ; Yunfeng, Li ; Shi Jingzhuo ; Ning, Guo
Author_Institution :
Dept. of Electr. Eng., Harbin Inst. of Technol., China
fYear :
2003
fDate :
24-26 Aug. 2003
Firstpage :
99
Lastpage :
102
Abstract :
A novel layered strategy based on the population hierarchic-rank is put forth considering the relation between the diversity of evolution population and evolution times. A developed genetic algorithm based on it is presented in this paper. Application in parameter identification of the single-phase AC series-excited motor (SACSM) testing shows that the algorithm presented in this paper is efficient comparing to the simple genetic algorithm and its modified algorithm. Not only can the algorithm converge to global optimal solution but also it improves the speed of convergence.
Keywords :
AC motors; genetic algorithms; machine testing; parameter estimation; algorithm convergence; evolution population; evolution times; genetic algorithm; global optimal solution; layered strategy; parameter identification; population hierarchic-rank; single-phase AC series-excited motor; AC motors; Genetic algorithms; Inductance; Magnetic flux; Mathematical model; Mathematics; Parameter estimation; System testing; Torque; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Diagnostics for Electric Machines, Power Electronics and Drives, 2003. SDEMPED 2003. 4th IEEE International Symposium on
Print_ISBN :
0-7803-7838-5
Type :
conf
DOI :
10.1109/DEMPED.2003.1234554
Filename :
1234554
Link To Document :
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