We describe performance improvement techniques for a multiple model adaptive estimator (MMAE) used to detect and identify control surface and sensor failures on an unmanned flight vehicle. Initially failure identification was accomplished within 4 s of onset, but by removing the "/spl beta/ dominance" effects, bounding the hypothesis conditional probabilities, retuning the Kalman filters, increasing the penalty for measurement residuals, decreasing the probability smoothing, and increasing residual propagation, the identification time was reduced to 2 s.<>


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    Title :

    Performance enhancement of a multiple model adaptive estimator


    Contributors:


    Publication date :

    1995-10-01


    Size :

    9751462 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English