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

Vincent Laurain (1) , Roland Toth (2) , Marion Gilson (1) , Hugues Garnier (1)

1 CRAN - Centre de Recherche en Automatique de Nancy
2 DCSC - Delft Center for System and Control

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.

Mots clés: LPV models; system identification; Refined Instrumental Variable; Box–Jenkins models; Input/Ouput; transfer function

Domaines: Automatique / Robotique

Vincent Laurain, Roland Toth, Marion Gilson, Hugues Garnier. Refined instrumental variable methods for identification of LPV Box–Jenkins models. Automatica, 2010, 46 (6), pp.959-967. ⟨10.1016/j.automatica.2010.02.026⟩. ⟨hal-00508675⟩