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Nonlinear Actuator Fault Detection for Small-Scale UASs

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Abstract

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 corresponding 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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Authors and Affiliations

  1. Australian Research Center for Aerospace Automation (ARCAA) and Queensland University, of Technology (QUT), Brisbane, Australia

    X. Yang, L. Mejias, F. Gonzalez, M. Warren & B. Arain

  2. School of Electrical Engineering and Computer Science, QUT, Brisbane, Australia

    B. Upcroft

Authors
  1. X. Yang
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  2. L. Mejias
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  3. F. Gonzalez
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  4. M. Warren
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  5. B. Upcroft
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  6. B. Arain
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Correspondence to X. Yang.

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Yang, X., Mejias, L., Gonzalez, F. et al. Nonlinear Actuator Fault Detection for Small-Scale UASs. J Intell Robot Syst 73, 557–572 (2014). https://doi.org/10.1007/s10846-013-9940-5

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  • DOI: https://doi.org/10.1007/s10846-013-9940-5

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