A combined MAP and Bayesian scheme for finite data and/or moving horizon estimation

Title: A combined MAP and Bayesian scheme for finite data and/or moving horizon estimation
Creator: Delgado, Ramón A.; Goodwin, Graham C.
Relation: Automatica Vol. 50, Issue 4, p. 1116-1121
Publisher Link: http://dx.doi.org/10.1016/j.automatica.2014.02.001
Publisher: Pergamon Press
Resource Type: journal article
Date: 2014
Description: Finite data and moving horizon estimation schemes are increasingly being used for a range of practical problems. However, both schemes suffer from potential conceptual difficulties. In the case of finite data, most of the methods in common use, excluding Bayesian strategies, depend upon asymptotic results. On the other hand, in the case of moving horizon estimation, there are two associated problems, namely (i) estimation error quantification is typically not available as a part of the solution and (ii) one needs to provide some form of prior state estimate (the so-called arrival cost). The current paper proposes a combined MAP–Bayesian scheme which, inter alia, addresses the finite data and moving horizon problems described above. The scheme combines MAP and Bayesian strategies. The efficacy of the method is illustrated via numerical examples.
Subject: moving horizon estimation; nonlinear filtering
Identifier: http://hdl.handle.net/1959.13/1053290
Identifier: uon:15557
Identifier: ISSN:0005-1098
Language: eng
Full Text
Reviewed

		Thumbnail	File	Description	Size	Format
View Details Download			ATTACHMENT02	Author final version	473 KB	Adobe Acrobat PDF	View Details Download