A UKF-based estimation strategy for actuator fault detection of UASs

Yang, Xilin, Warren, Michael, Arain, Bilal, Upcroft, Ben, Gonzalez, Luis Felipe, & Mejias, Luis (2013) A UKF-based estimation strategy for actuator fault detection of UASs. In Proceedings of the 2013 International Conference on Unmanned Aircraft Systems, ICUAS, IEEE Control Society, Atlanta, Georgia, pp. 516-525.

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This paper presents a recursive strategy for online detection of actuator faults on a unmanned aerial system (UAS) subjected to accidental actuator faults. The proposed detection algorithm aims to provide a UAS with the capability of identifying and determining characteristics of actuator faults, offering necessary flight information for the design of fault-tolerant mechanism to compensate for the resultant side-effect when faults occur. The proposed fault detection strategy consists of a bank of unscented Kalman filters (UKFs) with each one detecting a specific type of actuator faults and estimating correspond- ing velocity and attitude information. Performance of the proposed method is evaluated using a typical nonlinear UAS model and it is demonstrated in simulations that our method is able to detect representative faults with a sufficient accuracy and acceptable time delay, and can be applied to the design of fault-tolerant flight control systems of UASs.

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4 citations in Scopus
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3 citations in Web of Science®

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ID Code: 60681
Item Type: Conference Paper
Refereed: Yes
Additional Information: Authors are encouraged to accompany their presentations with multimedia material (i.e., videos), which will be included in the Conference Digital Proceedings. Conference Proceedings will be acquired by the IEEE CSS.
Authors of accepted papers will be invited to submit significantly different versions of the ICUAS'13 papers to the Journal of Intelligent and Robotic Systems (JINT), which will be published in a JINT Special Volume and in a Special Volume Book as part of the Springer series on Intelligent Systems, Control and Automation (ISCA).
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Keywords: UAV Forced Landing, UAS, UAV, Vision-Based Forced Landing, Detection, Actuator faults, Unmanned aerial vehicles, Accidental actuator faults, Fault-tolerant mechanism
DOI: 10.1109/ICUAS.2013.6564728
ISBN: 978-1-4799-0817-2
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
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 IEEE
Copyright Statement: Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Final version of the publication can be found at http://ieeexplore.ieee.org/
Deposited On: 08 Jul 2013 03:28
Last Modified: 14 Sep 2016 00:04

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