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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    Titel :

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


    Beteiligte:
    Yang, Xilin (Autor:in) / Warren, Michael (Autor:in) / Arain, Bilal (Autor:in) / Upcroft, Ben (Autor:in) / Gonzalez, Felipe (Autor:in) / Mejias, Luis (Autor:in)


    Erscheinungsdatum :

    01.05.2013


    Format / Umfang :

    1866550 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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