Third-order cumulants based methods for continuous-time errors-in-variables model identification

Stéphane Thil (1) , Hugues Garnier (1) , Marion Gilson (1)

1 CRAN - Centre de Recherche en Automatique de Nancy

In this paper, the problem of identifying stochastic linear continuous-time systems from noisy input/output data is addressed. The input of the system is assumed to have a skewed probability density function, whereas the noises contaminating the data are assumed to be symmetrically distributed. The third-order cumulants of the input/output data are then (asymptotically) insensitive to the noises, that can be colored and/or mutually correlated. Using this noise-cancellation property two computationally simple estimators are proposed. The usefulness of the proposed algorithms is assessed through a numerical simulation.

Mots clés: System identification; errors-in-variables; continuous-time systems; higher-order statistics

Domaines: Automatique / Robotique

Stéphane Thil, Hugues Garnier, Marion Gilson. Third-order cumulants based methods for continuous-time errors-in-variables model identification. Automatica, 2008, 44 (3), pp.647-658. ⟨10.1016/j.automatica.2007.07.010⟩. ⟨hal-00152696⟩