Title :
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
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;
Conference_Titel :
Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4253-4
DOI :
10.1109/ICIPS.1997.672855
