Robust actuator fault diagnosis algorithm for autonomous hexacopter UAVs

Antonio Gonzalez Rot*, Agus Hasan*, Poramate Manoonpong*

*Corresponding author for this work

Research output: Contribution to journalConference articleResearchpeer-review

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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 languageEnglish
Book seriesIFAC-PapersOnLine
Volume53
Issue number2
Pages (from-to)682-687
ISSN2405-8971
DOIs
Publication statusPublished - 2020
Event21st IFAC World Congress 2020 - Berlin, Germany
Duration: 12. Jul 202017. Jul 2020

Conference

Conference21st IFAC World Congress 2020
Country/TerritoryGermany
CityBerlin
Period12/07/202017/07/2020

Keywords

  • Fault diagnosis
  • Kalman filter
  • Unmanned Aerial Vehicles (UAVs)

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