Fast state estimation in nonlinear parametric time dependent systems using Tensor Train

Damiano Lombardi (1)

1 COMMEDIA - COmputational Mathematics for bio-MEDIcal Applications

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.

Mots clés: State Estimation; Reduced-order modelling; Tensor Train

Domaines: Modélisation et simulation

Damiano Lombardi. Fast state estimation in nonlinear parametric time dependent systems using Tensor Train. 2021. ⟨hal-03375811v1⟩