State estimation and diagnosis of uncertain systems based on an interval approach

Benoît Marx (1) , Didier Maquin (1) , José Ragot (1)

1 CRAN - Centre de Recherche en Automatique de Nancy

This paper deals with state estimation and fault detection in the presence of unknown but bounded state pertur- bations and measurement noise. In this context, most available results are for linear models. Based on interval analysis, a state estimator for nonlinear dynamical systems is presented. Given the perturbation and noise bounds, the proposed method evaluates a set estimate guaranteed to contain all values of the state that are consistent with the available observations. The estimator is then used to regime shift detection. A numerical example is given.

Domains: Automatic

Benoît Marx, Didier Maquin, José Ragot. State estimation and diagnosis of uncertain systems based on an interval approach. Conference on Control and Fault-Tolerant Systems, SysTol'10, Oct 2010, Nice, France. pp.CDROM, ⟨10.1109/SYSTOL.2010.5676036⟩. ⟨hal-00525124⟩