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Modified unscented recursive nonlinear dynamic data reconciliation for constrained state estimation

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Title Modified unscented recursive nonlinear dynamic data reconciliation for constrained state estimation
 
Creator KADU, SC
BHUSHAN, M
GUDI, RD
ROY, K
 
Subject urnddr
kalman filter
 
Description In state estimation problems, often, the true states satisfy certain constraints that need to be incorporated during the estimation procedure. Amongst various constrained nonlinear state estimation algorithms proposed in literature, the unscented recursive nonlinear dynamic data reconciliation (URNDDR) proposed by Vachhani et al. ( 2006) seems to be promising since it is able to incorporate constraints while maintaining the recursive nature of estimation. In this article, we propose a modified URNDDR algorithm that gives superior performance compared to basic URNDDR. The improvements are obtained via better constraint handling and are demonstrated via a representative case study.
 
Publisher ELSEVIER SCIENCE BV
 
Date 2011-10-22T03:49:10Z
2011-12-15T09:10:42Z
2011-10-22T03:49:10Z
2011-12-15T09:10:42Z
2009
 
Type Proceedings Paper
 
Identifier 10TH INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING: PART A,27,1335-1340
978-0-444-53472-9
1570-7946
http://dspace.library.iitb.ac.in/xmlui/handle/10054/14813
http://hdl.handle.net/100/1602
 
Source 10th International Symposium on Process Systems Engineering,Salvador, BRAZIL,AUG 16-20, 2009
 
Language English