Sensor diagnosis and state estimation for a class of skew symmetric time-varying systems

被引：6

作者：

Rafaralahy, Hugues ^{[1
]}

Richard, Edouard ^{[1
]}

Boutayeb, Mohamed ^{[1
]}

Zasadzinski, Michel ^{[1
]}

机构：

[1] Univ Lorraine, CRAN CNRS UMR 7039, F-54400 Longwy, France

来源：

AUTOMATICA | 2012年 / 48卷 / 09期

关键词：

Linear time-varying systems; State estimation; Fault reconstruction; Residual generation; Sensor fault; FAULT-DIAGNOSIS; RESIDUAL GENERATION; OBSERVER; BIAS;

D O I：

10.1016/j.automatica.2012.06.029

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this contribution we investigate the problem of simultaneous observer based sensor fault reconstruction and state estimation of a class of linear time-varying (LTV) systems that are skew-symmetric models. The main features concern the use of a bank of observers to detect and isolate faulty sensors and in the same time provide unbiased state estimation. On the other hand, we introduced a switching gain technique to deal with singular points. Stability analysis is achieved thanks to the Barbalat's lemma and without solving the well-known time-varying Sylvester equation. The proposed approach is extended to more general LTV systems of any order. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：2284 / 2289

页数：6

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