A Comparison of Least Squares Algorithms for Estimating Markov Parameters

被引：0

作者：

Fledderjohn, Matthew S. ^{[1
]}

Holzel, Matthew S. ^{[1
]}

Palanthandalam-Madapusi, Harish J. ^{[2
]}

Fuentes, Robert J. ^{[3
]}

Bernstein, Dennis S. ^{[4
]}

机构：

[1] Univ Michigan, Ann Arbor, MI 48109 USA

[2] Syracuse Univ, Dept Mech & Aerosp Engn, Syracuse, NY 13244 USA

[3] Flight Ctrl Dept, Raytheon Missle Syst, Tucson, AZ USA

[4] Univ Michigan, Dept Aerosp Engn, Ann Arbor, MI USA

来源：

2010 AMERICAN CONTROL CONFERENCE | 2010年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The purpose of this work is to compare model structures and identification algorithms for estimating Markov parameters in the presence of uncorrelated and correlated input, process, and output noise. We consider several least-squares variants with ARX and mu-Markov model structures, which are compared with white noise identification signals.

引用

页码：3735 / 3740

页数：6

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