2004
DOI: 10.1049/ip-cta:20041051
|View full text |Cite
|
Sign up to set email alerts
|

Set-valued estimation approach to recursive robust H∞ filtering

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
14
0

Year Published

2006
2006
2018
2018

Publication Types

Select...
8

Relationship

0
8

Authors

Journals

citations
Cited by 29 publications
(14 citation statements)
references
References 21 publications
0
14
0
Order By: Relevance
“…The topic of set-membership filtering has attracted a growing research interest, since it is based only on the knowledge of the hard bounds of the process and measurement noises [3,6,8,10,13,14,[16][17][18][19][20][21]29]. The idea of set-membership filtering is to provide all possible state estimates that are characterised by the set of state estimates consistent with both the observations received and the unknown but bounded process and measurement noises [3,10,20].…”
Section: Introductionmentioning
confidence: 99%
See 2 more Smart Citations
“…The topic of set-membership filtering has attracted a growing research interest, since it is based only on the knowledge of the hard bounds of the process and measurement noises [3,6,8,10,13,14,[16][17][18][19][20][21]29]. The idea of set-membership filtering is to provide all possible state estimates that are characterised by the set of state estimates consistent with both the observations received and the unknown but bounded process and measurement noises [3,10,20].…”
Section: Introductionmentioning
confidence: 99%
“…Hence the set-membership filtering problem aims to find the smallest characterisation of the feasible set of the states, rather than providing the most possible states under some optimality criteria, for example, Kalman filtering [2,27,33,34,36,38] and H 1 filtering [28,30,32]. Set-membership filtering is also called set-value filtering as the actual estimate is a set in state space rather than a single vector [14], [17], [21]. 0018-9251/09/$26.00 c°2009 IEEE Set-membership filtering problem was first considered by Witsenhausen [29].…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Ghaoui and Calafiore (2001), the convex optimization method has been employed to deal with the set-membership filtering for a class of norm bounded uncertainty system. In Ra, Jin, and Park (2004) and Savkin and Petersen (1995,9), a recursive method for constructing an ellipsoid state estimation set which is consistent with the measured output and the given noise has been proposed. The set-membership filtering problems have been investigated in Xia, Yang, and Han (2016) and Wei et al (2015) for a class of discrete time-varying systems with partial information transmission or with incomplete measurements.…”
Section: Set-membership Filtering For a Linear Systemmentioning
confidence: 99%
“…Most publications on SMF deal with linear systems [7], [9], [13], [14], [18], [19], [22], [23], [25], [28]. Only a few consider nonlinear systems [20], [26], as it is not straightforward to use the EKF method where the nonlinear dynamics are linearized around a state estimate point by a first-order Taylor series approximation.…”
Section: Introductionmentioning
confidence: 99%