An adaptive modified two-stage linear Kalman filtering algorithm is utilized to identify the loss of control effectiveness and the magnitude of low degree of stuck faults in a closed-loop nonlinear B747 aircraft. Control effectiveness factors and stuck magnitudes are used to quantify faults entering control systems through actuators. Pseudorandom excitation inputs are used to help distinguish partial loss and stuck faults. The partial loss and stuck faults in the stabilizer are isolated and identified successfully.
Actuator Fault Diagnosis in a Boeing 747 Model via Adaptive Modified Two-Stage Kalman Filter
2014
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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FAULT DIAGNOSIS FOR SENSOR AND ACTUATOR OF HEXACOPTER UAV USING DUAL EXTENDED KALMAN FILTER
British Library Conference Proceedings | 2022
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