In this paper, we propose a novel approach for Failure Detection and Identification (FDI) in nonlinear systems based on the Interacting Multiple Model (IMM) Extended Kalman Filter (EKF) approach. In the nonlinear-system FDI application, the main idea consists of representing each failure mode by a model and combining the outputs of EKF’s based on different models in a near-optimal way. This IMM-FDI filter provides not only failure detection and identification but also a near-optimal estimate of the system state (even during a failure). The approach has been applied successfully to a problem of spacecraft autonomy for the detection and identification of sensor (gyro, star tracker) and actuator failures. The results of this application show that IMM-EKF detects and identifies failures much more rapidly and reliably than the multi-hypothesis EKF. Furthermore, it handles satisfactorily both permanent and transient failures.


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    Titel :

    Autonomous failure detection, identification and fault-tolerant estimation for spacecraft guidance, navigation and control


    Beteiligte:
    Mehra, R. (Autor:in) / Rago, C. (Autor:in) / Seereeram, S. (Autor:in) / Bayard, David S. (Autor:in) / El-Genk, Mohamed S. (Herausgeber:in) / Bragg, Mary J. (Herausgeber:in)

    Kongress:

    Space technology and applications international forum - 1998 ; 1998 ; Albuquerque,New Mexico (USA)


    Erschienen in:

    AIP Conference Proceedings ; 420 , 1 ; 134-140


    Erscheinungsdatum :

    15.01.1998


    Format / Umfang :

    7 pages





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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