Affiliations: [a] Department of Civil Engineering, Xi'an Jiaotong
University, Xi'an, Shaanxi, China | [b] State Key Laboratory for Mechanical Behaviour of
Materials, Xi'an Jiaotong University, Xi'an, Shaanxi, China | [c] School of Aerospace, Xi'an Jiaotong University, Xi'an,
Shaanxi, China | Université Laval, Canada | Tohoku University, Japan
Correspondence:
[*]
Corresponding author: Qing Sun, Department of Civil Engineering,
Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China. E-mail:
sunq@mail.xjtu.edu.cn
Abstract: Hysteresis is an important nonlinear effect exhibited by the Macro
Fiber Composite (MFC) that is testified from experimental study. In order to
interpret the characteristic accurately, various models were proposed
previously, in which the Bouc-Wen model has gained more interest because of its
capability to match a wide class of hysteretic systems. However the model
consists of a set of differential equations where multi parameters present need
to be estimated simultaneously. In view of this, the present study sets out to
propose a more efficient Genetic Algorithm (GA) and a simplified Bouc-Wen model
on the one hand, and on the other, the GA is applied to the model to enhance
the accuracy and efficiency of the parameter estimation. Finally a large number
of experimental data are used to testify the proposed approach more efficient
and accurate than the other conventional methods. Also suggested are the
implications of the present study on other hysteretic models or other complex
mathematical models.
