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
2017-10-05
Article (Journal)
Electronic Resource
English
Discrete-time systems , Drone aircraft , Ice , Failure time data analysis , Fault diagnosis , Icing diagnosis , Linear parameter varying (LPV) systems , Unknown input observers (UIOs) , Unmanned aerial vehicles (UAVs) , Sistemes de temps discret , Avions no tripulats , Glaç , Temps entre fallades , Anàlisi del
DDC: | 629 |
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