Fault detection using Upper Bound Interval Kalman Filter for unmaned aerial vehicle

Carine Jauberthie (1) , Soheib Fergani (1) , Emelyne Saulnier (1)

1 LAAS-DISCO - Équipe DIagnostic, Supervision et COnduite

This paper deals with dynamics estimation and fault detection of unmaned aerial vehicles (uav) using the Upper Bound Interval Kalman Filter (UBIKF). An upper bound for all positive semi-definite matrices included in an interval matrix is calculated. This upper bound is used to generate envelopes for the variables to be estimated which are the dynamics of the UAV. It allows to provide a guaranteed estimation envelope for the considered dynamics. Then, the fault detection scheme is used based on a χ2 test. The faults concern sensors and actuators. Simulations on a discrete uncertain UAV model highlight the efficiency of the proposed filter for both UAV dynamics estimation and fault detection.

Mots clés: Upper bound; Fault detection; Simulation; Estimation; Autonomous aerial vehicles; Robustness; Real-time systems

Domaines: Systèmes dynamiques [math.DS]; Analyse numérique [math.NA]; Optimisation et contrôle [math.OC]; Traitement du signal et de l'image [eess.SP]; Automatique / Robotique; Santé publique et épidémiologie

Carine Jauberthie, Soheib Fergani, Emelyne Saulnier. Fault detection using Upper Bound Interval Kalman Filter for unmaned aerial vehicle. 2021 9th International Conference on Systems and Control (ICSC), Nov 2021, Caen, France. pp.101-106, ⟨10.1109/ICSC50472.2021.9666625⟩. ⟨hal-03685779⟩