Implementation of Grey-Box Identification in JModelica.org
(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:
http://lup.lub.lu.se/student-papers/record/4465456
- author
- Palmkvist, Elias
- supervisor
- organization
- year
- 2014
- 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}}, }