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.<>
Performance enhancement of a multiple model adaptive estimator
IEEE Transactions on Aerospace and Electronic Systems ; 31 , 4 ; 1240-1254
01.10.1995
9751462 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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