基于ARMA时序模型的结构参数识别集员算法

王晓军; 邱志平; 武哲

基于ARMA时序模型的结构参数识别集员算法

北京航空航天大学航空科学与工程学院, 北京 100083

基金项目: 国家杰出青年科学基金资助项目(10425208); 高等学校学科创新引智计划资助项目(B07009); 航空科学基金资助项目(2007ZA51003)

详细信息

作者简介:
王晓军(1978-),男,陕西岐山人,博士后,XJWang@buaa.edu.cn.

中图分类号: TB 123
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出版历程
- 收稿日期: 2006-12-04
- 网络出版日期: 2007-11-30

Set-membership algorithm for identification of structural parameters based on ARMA time-series model

School of Aeronautic Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

摘要

摘要: 研究在时域内利用含噪声观测数据识别结构参数问题.建立了与结构振动微分方程等价的自回归滑动平均(ARMA, Autoregressive Moving-Average)时序模型,将结构参数识别问题转换为ARMA模型参数辨识问题.在不确定但有界(UBB, Unknown-But-Bounded)噪声假设下,基于线性时不变系统参数集员辨识的区间算法,寻求与观测数据和噪声相容的参数的最小超长方体(或区间向量),进而得到结构参数的估计值.通过数值算例,将本文算法与最小二乘算法进行了比较,显示了其可行性和有效性.
- 结构参数识别 /
- 集员辨识 /
- 自回归滑动平均模型 /
- 区间数学 /
- 不确定但有界
Abstract: Identification of structural parameters by using observation data with noise in time domain was studied. Autoregressive moving-average (ARMA) model of a vibrating structure was established, and the identification problem of structural parameters was transformed into the identification problem of parameters of ARMA model. Based on the assumption of the unknown-but-bounded (UBB) noise, an interval algorithm for set-membership identification of parameters of linear time-invariant system was used to seek the minimal hyper-rectangle (or interval vector) of parameters, which is compatible with the measurements and the bounded noise, so that the structural parameters can be obtained. The numerical example illustrates its feasibility and effectiveness in comparison with the least squares algorithm.
- structural parameter identification /
- set-membership identification /
- autoregressive moving-average model /
- interval mathematics /
- unknown-but-bounded

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参考文献(1)

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