Kalman filtering for multiple time-delay systems

被引：171

作者：

Lu, X

Zhang, HS

Wang, W

Teo, KL

机构：

[1] Harbin Inst Technol, Shenzhen Grad Sch, Xili 518055, Shenzhen, Peoples R China

[2] Dalian Univ Technol, Res Ctr Informat & Control, Dalian 116023, Peoples R China

[3] Hong Kong Polytech Univ, Dept Appl Math, Hong Kong, Hong Kong, Peoples R China

来源：

AUTOMATICA | 2005年 / 41卷 / 08期

基金：

中国国家自然科学基金;

关键词：

discrete-time systems; delayed measurements; optimal filtering; innovation analysis; Riccati equations;

D O I：

10.1016/j.automatica.2005.03.018

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper is to study the linear minimum variance estimation for discrete-time systems with instantaneous and l-time delayed measurements by using re-organized innovation analysis. A simple approach to the problem is presented in this paper. It is shown that the derived estimator involves solving l + 1 different standard Kalman filtering with the same dimension as the original system. (C) 2005 Elsevier Ltd. All rights reserved.

引用

页码：1455 / 1461

页数：7

共 12 条

[1]

Anderson B., 1979, OPTIMAL FILTERING

[2]

[Anonymous], 1999, LINEAR ESTIMATION

[3]

KLEIN L.A., 1999, SENSOR DATA FUSION C

[4]

Kojima A, 2001, IEEE DECIS CONTR P, P991, DOI 10.1109/CDC.2001.980239