Abstract
This paper presents a robust actuator fault diagnosis algorithm for hexacopter Unmanned Aerial Vehicles (UAVs). The algorithm, based on Adaptive eXogenous Kalman Filter (AXKF), consists of two-stage operations: (i) a nonlinear observer and (ii) a linearized adaptive Kalman filter. To this end, we provide a sufficient condition for the nonlinear observer and recursive formulas for the linearized adaptive Kalman filter. The algorithm is tested for actuator fault diagnosis of a hexacopter UAV. Simulation results show that the proposed cascaded algorithm is able to accurately estimate the magnitude of the actuator fault.
Original language | English |
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Book series | IFAC-PapersOnLine |
Volume | 53 |
Issue number | 2 |
Pages (from-to) | 682-687 |
ISSN | 2405-8971 |
DOIs | |
Publication status | Published - 2020 |
Event | 21st IFAC World Congress 2020 - Berlin, Germany Duration: 12. Jul 2020 → 17. Jul 2020 |
Conference
Conference | 21st IFAC World Congress 2020 |
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Country/Territory | Germany |
City | Berlin |
Period | 12/07/2020 → 17/07/2020 |
Keywords
- Fault diagnosis
- Kalman filter
- Unmanned Aerial Vehicles (UAVs)