Göm meny

Abstract



Observer Design and Model Augmentation for Bias Compensation With a Truck Engine Application


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.

Erik Höckerdal, Erik Frisk and Lars Eriksson

Control Engineering Practice, 2009

External PDFShow BibTeX entry

Informationsansvarig: webmaster
Senast uppdaterad: 2019-06-05