DocumentCode
2571691
Title
Distributed receding horizon Kalman filter
Author
Maestre, J.M. ; Giselsson, P. ; Rantzer, A.
Author_Institution
Dept. of Syst. & Autom. Eng., Univ. of Seville, Seville, Spain
fYear
2010
fDate
15-17 Dec. 2010
Firstpage
5068
Lastpage
5073
Abstract
In this paper a distributed version of the Kalman filter is proposed. In particular, the estimation problem is reduced to the optimization of a cost function that depends on the system dynamics and the latest output measurements and state estimates which is distributed among the local subsystems by means of dual decomposition. The techniques presented in the paper are applied to estimate the position of mobile agents.
Keywords
Kalman filters; optimisation; state estimation; cost function; distributed receding horizon Kalman filter; dual decomposition; estimation problem; mobile agents; optimization; output measurements; state estimates; system dynamics; Cost function; Equations; Estimation; Kalman filters; Mathematical model; Trajectory;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location
Atlanta, GA
ISSN
0743-1546
Print_ISBN
978-1-4244-7745-6
Type
conf
DOI
10.1109/CDC.2010.5717370
Filename
5717370
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