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
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
收藏
页码:2284 / 2289
页数:6
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