Combined state and parameter estimation for a landslide model using Kalman filter

Mohit Mishra (1) , Gildas Besancon (1) , Guillaume Chambon (2) , Laurent Baillet (3)

1 GIPSA-MODUS - GIPSA - Modelling and Optimal Decision for Uncertain Systems
2 UR ETGR (ETNA) - Erosion torrentielle neige et avalanches
3 ISTerre - Institut des Sciences de la Terre

The paper presents a combined state and parameter estimation for a landslide model using a Kalman filter. The model under investigation is based on underlying mechanics that depicts a landslide behavior. This system is described by an Ordinary Differential Equation (ODE) with displacement as a state and landslide geometrical and material properties as parameters. The Kalman filter approach is utilized on a simplified model equation for state and parameter estimation. Finally, the presented approach is validated by two illustrative examples, the first one a synthetic case study and the second one on Super-Sauze landslide data taken from the literature.

Mots clés: State estimation; parameter estimation; Kalman filter; landslide model; Super-Sauze landslide

Domaines: Sciences de l'ingénieur [physics]; Sciences de l'environnement; Systèmes dynamiques [math.DS]

Mohit Mishra, Gildas Besancon, Guillaume Chambon, Laurent Baillet. Combined state and parameter estimation for a landslide model using Kalman filter. SYSID 2021 - 19th IFAC Symposium on System Identification (SYSID 2021), Jul 2021, Padoue (virtual), Italy. ⟨10.1016/j.ifacol.2021.08.376⟩. ⟨hal-03225544⟩