Fault Detection using Interval Kalman Filtering enhanced by Constraint Propagation - LAAS - Laboratoire d'Analyse et d'Architecture des Systèmes
Communication Dans Un Congrès Année : 2013

Fault Detection using Interval Kalman Filtering enhanced by Constraint Propagation

Résumé

In this paper, we consider an extension of conventional Kalman filtering to discrete time linear models with bounded uncertainties on parameters and gaussian measurement noise. To solve the interval matrix inversion problem involved in the equations of the Kalman filter and the over-bounding problem due to interval calculus, we propose an original approach combining the set inversion algorithm SIVIA and constraint propagation. The improved interval Kalman filter is applied in a fault detection schema illustrated by a simple case study.
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Dates et versions

hal-01966325 , version 1 (28-12-2018)

Identifiants

Citer

Jun Xiong, Carine Jauberthie, Louise Travé-Massuyès, Françoise Le Gall. Fault Detection using Interval Kalman Filtering enhanced by Constraint Propagation. Conference on Decision and Control, Dec 2013, Florence, Italy. ⟨10.1109/CDC.2013.6759929⟩. ⟨hal-01966325⟩
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