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
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