Constrained Kalman filter for Nonlinear structural identification

被引：0

作者：

Yang, YM ^{[1
]}

机构：

[1] Changsha Inst Technol, Dept Mechatron Engn & Instrumentat, Changsha, Peoples R China

来源：

WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL XVII, PROCEEDINGS: CYBERNETICS AND INFORMATICS: CONCEPTS AND APPLICATIONS (PT II) | 2001年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

It is well known that hysteresis is a principal source of internal energy dissipation in structural systems. The purpose of this paper is to show that constrained Kalman filtering can be effectively used to estimate the parameters in the differential model of hysteresis from experimental data. As a global weighted iteration method, constrained Kalman filtering can be highly efficient in system identification of inelastic structures from noisy data.

引用

页码：490 / 498

页数：3

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