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 an observer based on the default model. Three main results are a characterization of possible augmentations from observability perspectives, a parameterization of the augmentations from the method, and a robustness analysis of the proposed augmentation estimation method. The method is applied to a truck engine where the resulting augmented observer reduces the estimation bias by 50 % in a European transient cycle.
Observer design and model augmentation for bias compensation with a truck engine application
Beobachterentwurf und Modellerweiterung für die Fehlerkompensation mit Anwendung bei einem Nutzfahrzeugmotor
Control Engineering Practice ; 17 , 3 ; 408-417
2009
10 Seiten
Article (Journal)
English
Design and Application of the Series 60 Engine, Truck Applications
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