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 estim...
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Published in | Control engineering practice Vol. 17; no. 3; pp. 408 - 417 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.03.2009
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Subjects | |
Online Access | Get full text |
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Summary: | 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. |
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ISSN: | 0967-0661 1873-6939 1873-6939 |
DOI: | 10.1016/j.conengprac.2008.09.004 |