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 " 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
Betriebsverbesserung einer adaptiven Mehfachmodellabschätzung
IEEE Transactions on Aerospace and Electronic Systems ; 31 , 4 ; 1240-1254
1995
15 Seiten, 12 Quellen
Article (Journal)
English
Performance Enhancement of a Multiple Model Adaptive Estimator
Online Contents | 1995
|A Necessary Condition for Effective Performance of the Multiple Model Adaptive Estimator
Online Contents | 1995
|Spacecraft autonomous navigation using multiple model adaptive estimator
Emerald Group Publishing | 2015
|