This paper proposes a discrete-time linear parameter varying (LPV) unknown input observer (UIO) for the diagnosis of actuator faults and ice accretion in unmanned aerial vehicles (UAVs). The proposed approach, which is suited to an implementation on-board, exploits a complete 6-degrees of freedom (DOF) UAV model, which includes the coupled longitudinal/lateral dynamics and the impact of icing. The LPV formulation has the advantage of allowing the icing diagnosis scheme to be consistent with a wide range of operating conditions. The developed theory is supported by simulations illustrating the diagnosis of actuator faults and icing in a small UAV. The obtained results validate the effectiveness of the proposed approach. ; Peer Reviewed ; Postprint (published version)
Diagnosis of icing and actuator faults in UAVs using LPV unknown input observers
05.10.2017
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Failure time data analysis , Glaç , Discrete-time systems , Sistemes de temps discret , Unmanned aerial vehicles (UAVs) , Fault diagnosis , Drone aircraft , Temps entre fallades , Icing diagnosis , Unknown input observers (UIOs) , Anàlisi del , Avions no tripulats , Ice , Linear parameter varying (LPV) systems
DDC: | 629 |
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Springer Verlag | 2024
|ArXiv | 2017
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