DocumentCode :
514993
Title :
Parameter Identification and Simulation of the Noise-Involved Hysteretic Model Using Improved Genetic Algorithm
Author :
Xue Xiaomin ; Zhang Ling ; Sun Qing
Author_Institution :
Xi´an Jiaotong Univ., Xian, China
Volume :
2
fYear :
2010
fDate :
13-14 March 2010
Firstpage :
868
Lastpage :
871
Abstract :
Hysteresis is a specific character of a wide range of physical systems and devices, such as electromagnetic fields, mechanical stress-strain elements, and electronic relay circuits. The extended Bouc-Wen model is one of the most widely accepted phenomenological models of hysteresis in mechanics. However the multi parameters have plagued its further application because the capability of computer and algorithm available currently can not meet the need completely. Thus to exploit an efficient and accurate parallel algorithm is very essential and significant. This paper is committed to propose an improved genetic algorithm (GA) so as to identify the parameter of the Bouc-Wen model effectively. Finally a large amount of noise-involved data is employed to verify the proposed approach is very effective and accurate.
Keywords :
computational electromagnetics; electromagnetic fields; genetic algorithms; parallel algorithms; parameter estimation; electromagnetic fields; electronic relay circuits; extended Bouc-Wen model; hysteresis; improved genetic algorithm; mechanical stress strain elements; noise involved hysteretic model; parallel algorithm; parameter identification; phenomenological models; Curve fitting; Electromagnetic measurements; Genetic algorithms; Hysteresis; Mechanical variables measurement; Noise measurement; Parallel algorithms; Parameter estimation; Polynomials; Stress measurement; Improved GA; Parallel algorithm; Parameter identification; Phenomoneon model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
Conference_Location :
Changsha City
Print_ISBN :
978-1-4244-5001-5
Electronic_ISBN :
978-1-4244-5739-7
Type :
conf
DOI :
10.1109/ICMTMA.2010.482
Filename :
5460068
Link To Document :
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