Recursive actuator fault detection and diagnosis for emergency landing of UASs
Yang, Xilin, Mejias, Luis, Warren, Michael, Gonzalez, Felipe, & Upcroft, Ben (2014) Recursive actuator fault detection and diagnosis for emergency landing of UASs. In Proceedings of the19th World Congress of the International Federation of Automatic Control, International Federation of Automatic Control (IFAC), Cape Town, South Africa, pp. 2495-2502.
This paper presents a practical recursive fault detection and diagnosis (FDD) scheme for online identification of actuator faults for unmanned aerial systems (UASs) based on the unscented Kalman filtering (UKF) method. The proposed FDD algorithm aims to monitor health status of actuators and provide indication of actuator faults with reliability, offering necessary information for the design of fault-tolerant flight control systems to compensate for side-effects and improve fail-safe capability when actuator faults occur. The fault detection is conducted by designing separate UKFs to detect aileron and elevator faults using a nonlinear six degree-of-freedom (DOF) UAS model. The fault diagnosis is achieved by isolating true faults by using the Bayesian Classifier (BC) method together with a decision criterion to avoid false alarms. High-fidelity simulations with and without measurement noise are conducted with practical constraints considered for typical actuator fault scenarios, and the proposed FDD exhibits consistent effectiveness in identifying occurrence of actuator faults, verifying its suitability for integration into the design of fault-tolerant flight control systems for emergency landing of UASs.
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|Item Type:||Conference Paper|
|Keywords:||Fault Tolerant Systems, Emergency Landing, Forced Landing, UKF|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aircraft Performance and Flight Control Systems (090104)|
|Divisions:||Current > Research Centres > Australian Research Centre for Aerospace Automation
Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2014 [please consult the author]|
|Deposited On:||22 May 2014 23:32|
|Last Modified:||01 Nov 2014 07:00|
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