Identification of continuous-time errors-in-variables models

Kaushik Mahata (1) , Hugues Garnier (2)

1 Centre for Complex Dynamic Systems and Control
2 CRAN - Centre de Recherche en Automatique de Nancy

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 nonuniformly sampled data. The asymptotic distributions of the estimates are derived. The performances of the proposed algorithms are illustrated with some numerical simulation examples.

Mots clés: Errors-in-variables; system identification; continuous-time models; linear estimation

Domaines: Automatique / Robotique

Kaushik Mahata, Hugues Garnier. Identification of continuous-time errors-in-variables models. Automatica, 2006, 42 (9), pp.1470-1490. ⟨10.1016/j.automatica.2006.04.012⟩. ⟨hal-00119875⟩