Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/678
Title: A methodology to enhance the convergence of output error identification algorithms
Authors: Tohme, Elie Toni
Ouvrard, Regis
Abche, Antoine 
Trigeassou, Jean Claude
Poinot, Thierry
Mercère, Guillaume
Affiliations: Department of Electrical Engineering 
Keywords: Convergence
Filtering theory
Optimisation
Subjects: Parameter estimation
Issue Date: 2015
Publisher: IEEE
Part of: European Control Conference (ECC), 2007
Start page: 5721
End page: 5728
Conference: European Control Conference (ECC) (2-5 July 2007 : Kos, Greece) 
Abstract: 
In this work, a new off-line optimization approach is proposed to improve the global convergence. This algorithm, called Pseudo-Output Error (POE) algorithm, is based on the introduction of a stationary filter in the parametric sensitivity functions of the Gauss-Newton algorithm. The global convergence is assured for a first order system, what ever the stationary filter of the same order. Consequently, a partial fraction expansion of an nth order system into n first order systems in parallel is introduced. The identification of each individual system using the POE algorithm is globally convergent. The expansion introduces a filtering process and uses an a priori knowledge on the parameters that can bias the estimation process. However, the estimated parameters are close to the true parameters and are used to initialize the Gauss-Newton Output Error (OE) algorithm. The results of the performed simulations show the efficiency of the proposed approach. In particular, while the traditional OE algorithm diverges when it is applied directly to the system to be identified, the POE algorithm in conjunction with the decomposition of the system leads to a very good initialization for the OE algorithm. Consequently, the latter algorithm converges to the true parameters.
URI: https://scholarhub.balamand.edu.lb/handle/uob/678
Ezproxy URL: Link to full text
Type: Conference Paper
Appears in Collections:Department of Electrical Engineering

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