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Implementation of Grey-Box Identification in JModelica.org

Palmkvist, Elias (2014)
Department of Automatic Control
Abstract
Grey-box identification is a tool to identify and improve nonlinear system models by estimating parameters. The estimation is done by optimizing a cost function using measurement data. The robustness of the estimations can then be analyzed with statistics. JModelica.org is a platform for modeling and optimization of dynamical models. In order to do grey-box identification one need models and be able to optimize. JModelica.org supports modeling and optimization so it has a huge potential to support grey-box identification. So far there is no complete solution for grey-box identification in JModelica.org. This work is focusing on how to implement greybox identification in JModelica.org in order to estimate parameters for nonlinear models.... (More)
Grey-box identification is a tool to identify and improve nonlinear system models by estimating parameters. The estimation is done by optimizing a cost function using measurement data. The robustness of the estimations can then be analyzed with statistics. JModelica.org is a platform for modeling and optimization of dynamical models. In order to do grey-box identification one need models and be able to optimize. JModelica.org supports modeling and optimization so it has a huge potential to support grey-box identification. So far there is no complete solution for grey-box identification in JModelica.org. This work is focusing on how to implement greybox identification in JModelica.org in order to estimate parameters for nonlinear models. The theory of grey-box identification has been investigated as well as the possibilities with JModelica.org. Finally, an interactive method to estimate model
parameters and a method to calculate the confidence intervals for the estimates have been implemented. The implementation has been tested for nonlinear models and works as expected. (Less)
Please use this url to cite or link to this publication:
author
Palmkvist, Elias
supervisor
organization
year
type
H3 - Professional qualifications (4 Years - )
subject
ISSN
0280-5316
other publication id
ISRN LUTFD2/TFRT--5941--SE
language
English
id
4465456
date added to LUP
2014-06-13 11:13:28
date last changed
2014-06-13 11:13:28
@misc{4465456,
  abstract     = {{Grey-box identification is a tool to identify and improve nonlinear system models by estimating parameters. The estimation is done by optimizing a cost function using measurement data. The robustness of the estimations can then be analyzed with statistics. JModelica.org is a platform for modeling and optimization of dynamical models. In order to do grey-box identification one need models and be able to optimize. JModelica.org supports modeling and optimization so it has a huge potential to support grey-box identification. So far there is no complete solution for grey-box identification in JModelica.org. This work is focusing on how to implement greybox identification in JModelica.org in order to estimate parameters for nonlinear models. The theory of grey-box identification has been investigated as well as the possibilities with JModelica.org. Finally, an interactive method to estimate model
parameters and a method to calculate the confidence intervals for the estimates have been implemented. The implementation has been tested for nonlinear models and works as expected.}},
  author       = {{Palmkvist, Elias}},
  issn         = {{0280-5316}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Implementation of Grey-Box Identification in JModelica.org}},
  year         = {{2014}},
}