Thrust Fault Diagnosis Using Extended Kalman Filter Considering Dynamics of Lift-Cruise UAV

This study proposes an Extended Kalman Filter (EKF) that considers dynamics to diagnose thrust faults in lift-cruise type UAVs. A diagnostic logic, based on the residuals of roll and pitch rates calculated using EKF-estimated values, is devised to determine the location of thrust faults. The EKF also provides real-time estimates of the health values for each rotor. Numerical simulations validate the efficiency of the proposed fault diagnosis method, demonstrating its ability to rapidly identify fault locations.