A novel fault detection (FD) method for nonlinear systems using the residuals generated by the unscented Kalman filter (UKF) is proposed. The errors of the UKF are derived and sufficient conditions for the convergence of the UKF are presented. As the local approach is a powerful statistical technique for detecting changes in the mean of a Gaussian process, it is used to devise a hypothesis test to detect faults from residuals obtained from the UKF. Further, it is demonstrated that the selection of a sample number is important in improving the performance of the local approach. To illustrate the implementation and performance of the proposed technique, it is applied to detect sensor faults in the measurement of satellite attitude.


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    Title :

    Detection of satellite attitude sensor faults using the UKF


    Contributors:
    Xiong, K. (author) / Chan, C.W. (author) / Zhang, H.Y. (author)


    Publication date :

    2007-04-01


    Size :

    1543526 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Detection of satellite attitude sensor faults using the UKF

    Xiong, K. / Chan, C.W. / Zhang, H.Y. | Tema Archive | 2007


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