Structured model identification algorithm based on constrained optimisation

This article presents an identification algorithm dedicated to the estimation of the coefficients of physically-structured models. This algorithm is based on a constrained gradient-based optimisation that minimises a non-convex cost function to identify a structured model, starting from an initial b...

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Bibliographic Details
Published in2015 European Control Conference (ECC) pp. 1285 - 1290
Main Authors Vayssettes, J., Mercere, G., Bury, Y., Pommier-Budinger, V.
Format Conference Proceeding
LanguageEnglish
Published EUCA 01.07.2015
Subjects
Cost function
Estimation
Frequency-domain analysis
Optimization methods
Reliability
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DOI10.1109/ECC.2015.7330715

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Summary:This article presents an identification algorithm dedicated to the estimation of the coefficients of physically-structured models. This algorithm is based on a constrained gradient-based optimisation that minimises a non-convex cost function to identify a structured model, starting from an initial black-box model. The suggested method is able to handle linear relations between the model coefficients so as to identify a model with the desired physical structure. Since the minimised function is non-convex, the initial model must be in the neighbourhood of its global minimum. The initialisation issue is discussed and a total-least-squares-based solution is suggested. These new developments are evaluated on a simulation benchmark, illustrating the identification of a mechanical system.
DOI:10.1109/ECC.2015.7330715