A method identifying the parameters of Bounc-Wen hysteretic nonlinear model based on genetic algorithm

Author

Xueliang, Zhang ; Yumei, Huang ; Yongchao, Liu ; Xiaoyue, Wang ; Feng, Gao

Author_Institution

Dept. of Mech. Eng., Xian Univ. of Technol., China

Volume

1

fYear

1997

fDate

28-31 Oct 1997

Firstpage

602

Abstract

The Bounc-Wen model (Wen, 1976) is a typical hysteretic nonlinear model, and its parameter identification is very important. Existing identification methods depend heavily on the given initial values of the parameters. Based on the advantages of genetic algorithms (GA), this paper builds the fitness function corresponding to the problem and adopts the crossover and mutation between the gene code strings of the same variables, improving the convergence rate of GA. The example proves that this method is feasible

Keywords

convergence; genetic algorithms; hysteresis; nonlinear systems; parameter estimation; Bounc Wen model; convergence rate; crossover; fitness function; gene code strings; genetic algorithms; hysteretic nonlinear model; mutation; parameter identification; Computational modeling; Damping; Genetics; Hysteresis; Iterative algorithms; Iterative methods; Jacobian matrices; Least squares methods; Parameter estimation; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-4253-4

Type

conf

DOI

10.1109/ICIPS.1997.672855

Filename

672855