In this paper, a real-time approach to detect the faults affecting the mean and the covariance matrix of the Kalman filter innovation sequence is presented. The ratio of two quadratic forms for which the matrices are theoretical and selected covariance matrices, as monitoring statistics, is used. The arguments of the optimal quadratic form that maximize the above statistics are determined to detect the faults in sensors rapidly. The longitudinal dynamics of an aircraft control system, as an example, is considered, and detection of the faults in pitch gyroscope affecting the mean and the covariance matrix is examined.


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    Title :

    Sensor fault detection in flight control systems based on the Kalman filter innovation sequence


    Additional title:

    Sensorfehlererkennung in einem Flugregelungssystem auf der Basis der weißen Rauschsequenz eines Kalman-Filters


    Contributors:


    Publication date :

    1999


    Size :

    6 Seiten, 4 Bilder, 13 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English