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Performance comparison of the Extended Kalman Filter and the Recursive Prediction Error Method
Linköping University, Department of Electrical Engineering.
2003 (English)Independent thesis Basic level (professional degree)Student thesisAlternative title
Jämförelse mellan Extended Kalmanfiltret och den Rekursiva Prediktionsfelsmetoden (Swedish)
Abstract [en]

In several projects within ABB there is a need of state and parameter estimation for nonlinear dynamic systems. One example is a project investigating optimisation of gas turbine operation. In a gas turbine there are several parameters and states which are not measured, but are crucial for the performance. Such parameters are polytropic efficiencies in compressor and turbine stages, cooling mass flows, friction coefficients and temperatures. Different methods are being tested to solve this problem of system identification or parameter estimation. This thesis describes the implementation of such a method and compares it with previously implemented identification methods. The comparison is carried out in the context of parameter estimation in gas turbine models, a dynamic load model used in power systems as well as models of other dynamic systems. Both simulated and real plant measurements are used in the study.

Place, publisher, year, edition, pages
Institutionen för systemteknik , 2003. , 57 p.
Series
LiTH-ISY-Ex, 3351
Keyword [en]
Reglerteknik, Extended Kalman filter, Parameter estimation, Recursive prediction error methods
Keyword [sv]
Reglerteknik
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-1832OAI: oai:DiVA.org:liu-1832DiVA: diva2:19158
Uppsok
teknik
Available from: 2003-06-17 Created: 2003-06-17

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CiteExportLink to record
Permanent link

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