Identification of Bouc-Wen type models using multi-objective optimization algorithms

被引：48

作者：

Ortiz, Gilberto A. ^{[1
]}

Alvarez, Diego A. ^{[1
]}

Bedoya-Ruiz, Daniel ^{[1
]}

机构：

[1] Univ Nacl Colombia, Manizales 170004, Colombia

来源：

COMPUTERS & STRUCTURES | 2013年 / 114卷

关键词：

Bouc-Wen-Baber-Noori model; Hysteresis; Multi-objective optimization; System identification; NSGA-II; NONLINEAR HYSTERETIC SYSTEMS; RANDOM VIBRATION; PARAMETER-ESTIMATION; EQUIVALENT LINEARIZATION; VALIDATION; JOINTS; SLIP;

D O I：

10.1016/j.compstruc.2012.10.016

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Most of the published literature concerned with the parameter estimation of the Bouc-Wen model of hysteresis via evolutionary algorithms uses a single objective function (the mean square error between the known displacements and the estimated ones) and considers the original Bouc-Wen model of hysteresis (without degradation and pinching) in the identification process. in this paper, a novel method for the identification of the parameters of the Bouc-Wen-Baber-Noori (BWBN) model of hysteresis is presented. The methodology is based on a multi-objective evolutionary optimization algorithm called NSGA-II [39]; therefore, a set of objective functions is employed instead of the traditional single objective function. The proposed methodology identifies the structural system and allows the observation of multi-modality of the BWBN model of hysteresis. The performance of the algorithm is evaluated using simulated and real data. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：121 / 132

页数：12

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