A novel approach to model error modelling using the expectation-maximization algorithm

Title: A novel approach to model error modelling using the expectation-maximization algorithm
Creator: Delgado, Ramón A.; Goodwin, Graham C.; Carvajal, Rodrigo; Agüero, Juan C.
Relation: 51st IEEE Conference on Decision and Control, CDC 2012. Proceedings of the 51st IEEE Conference on Decision and Control (Maui, Hawaii 10-13 December, 2012) p. 7327-7332
Publisher Link: http://dx.doi.org/10.1109/cdc.2012.6426633
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Resource Type: conference paper
Date: 2012
Description: In this paper we develop a novel approach to model error modelling. There are natural links to others recently developed ideas. However, here we make several key departures, namely (i) we focus on relative errors; (ii) we use a broad class of model error description which includes, inter alia, the earlier idea of stochastic embedding; (iii) we estimate both, the nominal model and undermodelling simultaneously using the Expectation-Maximization (EM) algorithm. Simulation studies illustrate the performance of the proposed technique.
Subject: model error modelling; system identification; EM algorithm
Identifier: http://hdl.handle.net/1959.13/1053114
Identifier: uon:15527
Identifier: ISBN:9781467320665
Language: eng
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