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Abstract



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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