Estimation of Noise Means and Covariance Matrices for Linear Time-Varying Models

被引：0
|
作者：
Kost, Oliver [1 ,2 ]
Dunik, Jindrich [1 ,2 ]
Straka, Ondrej [1 ,2 ]
机构：
[1] Univ West Bohemia, Dept Cybernet, Fac Appl Sci, Univ 8, Plzen 30614, Czech Republic
[2] Univ West Bohemia, Res Ctr NTIS, Fac Appl Sci, Univ 8, Plzen 30614, Czech Republic
来源：
2018 ANNUAL AMERICAN CONTROL CONFERENCE (ACC) | 2018年
关键词：
Estimation; Identification; State-space models; Noise means; Noise Covariance Matrices; LEAST-SQUARES METHOD; IDENTIFICATION;
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 paper deals with the estimation of the means and covariance matrices of the noises of a linear time-varying system described by the state-space model. The proposed measurement difference method is based on a statistical analysis of differenced, linearly transformed, and shifted augmented measurement vector resulting in a system of linear matrix equations for consistent estimation of both; noise means and noise covariance matrices. The theoretical results are discussed and illustrated in a numerical example.
引用
收藏
页码：265 / 271
页数：7
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