2009
DOI: 10.1137/070700322
|View full text |Cite
|
Sign up to set email alerts
|

Unknown Input and State Estimation for Unobservable Systems

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
63
0
1

Year Published

2009
2009
2022
2022

Publication Types

Select...
7
1

Relationship

1
7

Authors

Journals

citations
Cited by 76 publications
(64 citation statements)
references
References 16 publications
0
63
0
1
Order By: Relevance
“…Under the condition that the norm of the uncertain term ε(x, t) fulfills the restriction (29), the proposed estimation procedure given by (26), (28) provides the exact reconstruction of the binary vector δ in the time intervals t ∈ [t i−1 + t * , t i ), according to (30). would correspond, in the linear context, to locating the eigenvalues of the error dynamics far away from the origin.…”
Section: Lemmamentioning
confidence: 99%
See 1 more Smart Citation
“…Under the condition that the norm of the uncertain term ε(x, t) fulfills the restriction (29), the proposed estimation procedure given by (26), (28) provides the exact reconstruction of the binary vector δ in the time intervals t ∈ [t i−1 + t * , t i ), according to (30). would correspond, in the linear context, to locating the eigenvalues of the error dynamics far away from the origin.…”
Section: Lemmamentioning
confidence: 99%
“…Recently several methodologies have been proposed in the literature for the finite time reconstruction of unknown inputs based on higher-order sliding mode theory, via the so-called hierarchical HOSM observation approach [27,28]. In this paper a finite time observer based on the sub-optimal sliding mode algorithm will be suggested, which provides the exact unknown input reconstruction and a guaranteed convergence time in spite of model uncertainties.…”
Section: Introductionmentioning
confidence: 99%
“…39 Therefore, the method of finite-time estimation in section ''Finite time observation for strongly observable systems'' can be utilized to reconstruct "…”
Section: Construct Nonsingular Matrixmentioning
confidence: 99%
“…The first drawback has to do with the assumption that the system is strongly detectable but not strongly observable; therefore, a transformation must first be done in order to decompose the system into the strongly observable part and the detectable part (see, e.g. [16]). The second drawback has to do with the fact that, during the implementation of the differentiator, some errors appear due to the computation sample time and noises in the sensors.…”
Section: B Output Extension Via Hosm Differentiatormentioning
confidence: 99%
“…Some observers have been designed assuming that the Hautus condition is satisfied ( [10], [11], [2]). In some other works, a differentiation process was suggested, mainly based on first and second order sliding mode techniques ( [12], [3], [13], [14], [15], [16]). A method for the construction of a new output to fulfill the Hautus condition is suggested in [17].…”
Section: Introductionmentioning
confidence: 99%