Observer Design and Model Augmentation for Bias Compensation Applied to an Engine
A systematic design method for reducing bias in observers is
developed. The method utilizes an observable default model of the
system together with measurement data from the real system and
estimates a model augmentation. The augmented model is then used to
design an observer which reduces the estimation bias compared to a
default observer. A key result is the theoretical analysis that
characterizes the possible augmentations is also conducted. The
method is applied to a truck engine where the resulting augmented
observer reduces the estimation bias with 50% in an ETC.
Erik Höckerdal, Erik Frisk and Lars Eriksson
IFAC World Congress,
2008
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