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Bias Reduction in DAE Estimators by Model Augmentation: Observability Analysis and Experimental Evaluation
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
2011 (English)In: 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), 2011, Institute of Electrical and Electronics Engineers (IEEE), 2011, 7446-7451 p.Conference paper (Refereed)
Abstract [en]

A method for bias compensation in model based estimation utilizing model augmentation is developed. Based on a default model, that suffers from stationary errors, and measurements from the system a low order augmentation is estimated. The method handles models described by differential algebraic equations and the main contributions are necessary and sufficient conditions for the preservation of the observability properties of the default model during the augmentation. A characterization of possible augmentations found through the estimation, showing the benefits of adding extra sensors during the design, is included. This enables reduction of estimation errors also in states not used for feedback, which is not possible with for example PI-observers. Beside the estimated augmentation the method handles user provided augmentations, found through e.g. physical knowledge of the system. The method is evaluated on a nonlinear engine model where its ability to incorporate information from additional sensors during the augmentation estimation is clearly illustrated. By applying the method the mean relative estimation error for the exhaust manifold pressure is reduced by 55%.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2011. 7446-7451 p.
Series
Decision and Control (CDC), ISSN 0191-2216, E-ISSN 0743-1546
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:liu:diva-137785DOI: 10.1109/CDC.2011.6160697ISBN: 978-1-61284-800-6 (print)ISBN: 978-1-61284-801-3 (electronic)ISBN: 978-1-4673-0457-3 (electronic)ISBN: 978-1-61284-799-3 (electronic)ISBN: 978-1-61284-799-3 (electronic)ISBN: 978-1-61284-800-6 (electronic)OAI: oai:DiVA.org:liu-137785DiVA: diva2:1102620
Conference
2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), Orlando, FL, USA, December 12-15, 2011
Available from: 2017-05-29 Created: 2017-05-29 Last updated: 2017-06-01Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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