Refined instrumental variable methods for identification of LPV Box-Jenkins models

Authors:
Vincent Laurain;Marion Gilson;Roland Tóth;Hugues Garnier
Affiliations:
Centre de Recherche en Automatique de Nancy (CRAN), Nancy-Université, CNRS, BP 70239, 54506 Vandoeuvre-les-Nancy Cedex, France;Centre de Recherche en Automatique de Nancy (CRAN), Nancy-Université, CNRS, BP 70239, 54506 Vandoeuvre-les-Nancy Cedex, France;Delft Center for Systems and Control (DCSC), Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands;Centre de Recherche en Automatique de Nancy (CRAN), Nancy-Université, CNRS, BP 70239, 54506 Vandoeuvre-les-Nancy Cedex, France
Venue:
Automatica (Journal of IFAC)
Year:
2010

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Abstract

The identification of linear parameter-varying systems in an input-output setting is investigated, focusing on the case when the noise part of the data generating system is an additive colored noise. In the Box-Jenkins and output-error cases, it is shown that the currently available linear regression and instrumental variable methods from the literature are far from being optimal in terms of bias and variance of the estimates. To overcome the underlying problems, a refined instrumental variable method is introduced. The proposed approach is compared to the existing methods via a representative simulation example.