State estimation in nonlinear parametric time dependent systems using Tensor Train
Résumé
In the present work we propose a reduced-order method to solve the state estimation problem when nonlinear parametric time-dependent systems are at hand. The method is based on the approximation of the set of system solutions by means of a Tensor Train format. The particular structure of Tensor Train makes it possible to set up both a variational and a sequential method. Several numerical experiments are proposed to assess the behaviour of the method.
Domaines
Modélisation et simulationOrigine | Fichiers produits par l'(les) auteur(s) |
---|