DocumentCode :
2261228
Title :
Solving Parameter Identification Problem of Nonlinear Systems Using Differential Evolution Algorithm
Author :
Wang, Ke ; Wang, Xiaodong ; Wang, Jinshan ; Jiang, Minlan ; Lv, Ganyun ; Feng, Genliang ; Xu, Xiuling
Author_Institution :
Dept. of Electron. Eng., Zhejiang Normal Univ., Jinhua
Volume :
1
fYear :
2008
fDate :
20-22 Dec. 2008
Firstpage :
687
Lastpage :
691
Abstract :
A new technique, based on differential evolution algorithm, is proposed for solving the parameter identification problem of nonlinear systems. The technique improves the accuracy of parameter identification. Two kinds of process systems have been used as examples for demonstration. The effectiveness of differential evolution algorithm is compared with that of genetic algorithms in terms of obtained parameter accuracy and objective function value. The simulation results show that the accurate estimation of unknown system parameters and small values of objective function can be achieved by the proposed technique.
Keywords :
genetic algorithms; nonlinear systems; parameter estimation; differential evolution algorithm; genetic algorithms; nonlinear systems; parameter identification problem; Artificial intelligence; Artificial neural networks; Control engineering; Genetic algorithms; Information technology; Least squares methods; Nonlinear systems; Parameter estimation; Polynomials; System identification; Differential Evolution; Nonlinear Systems; Parameter Identification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3497-8
Type :
conf
DOI :
10.1109/IITA.2008.556
Filename :
4739659
Link To Document :
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