Diagnosis of icing and actuator faults in UAVs using LPV unknown input observers
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 (D...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2017 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/113767 |
| Acceso en línea: | https://hdl.handle.net/2117/113767 https://dx.doi.org/10.1007/s10846-017-0716-1 |
| Access Level: | acceso abierto |
| Palabra clave: | 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 |
| Sumario: | 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. |
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