Identification of continuous-time errors-in-variables models

Authors:
Kaushik Mahata;Hugues Garnier
Affiliations:
Centre for Complex Dynamic Systems and Control, School of Electrical Engineering and Computer Science, University of Newcastle, Callaghan, NSW 2308, Australia;Centre de Recherche en Automatique de Nancy, CRAN UMR 7039 CNRS-INPL-UHP, Université Henri Poincaré, Nancy 1, BP 239, 54506 Vandoeuvre-les-Nancy Cedex, France
Venue:
Automatica (Journal of IFAC)
Year:
2006

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Abstract

A novel direct approach for identifying continuous-time linear dynamic errors-in-variables models is presented in this paper. The effects of the noise on the state-variable filter outputs are analyzed. Subsequently, a few algorithms to obtain consistent continuous-time parameter estimates in the errors-in-variables framework are derived. It is also possible to design search-free algorithms within our framework. The algorithms can be used for non-uniformly sampled data. The asymptotic distributions of the estimates are derived. The performances of the proposed algorithms are illustrated with some numerical simulation examples.