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A Framework for Nonlinear Model Predictive Control in JModelica.org

Axelsson, Magdalena; Magnusson, Fredrik LU and Henningsson, Toivo (2015) 11th International Modelica Conference In Proceedings of the 11th International Modelica Conference 2015 p.301-310
Abstract
Nonlinear Model Predictive Control (NMPC) is a control strategy based on repeatedly solving an optimal control problem. In this paper we present a new MPC framework for the JModelica.org platform, developed specifically for use in NMPC schemes. The new framework utilizes the fact that the optimal control problem to be solved does not change between solutions, thus decreasing the computation time needed to solve it. The new framework is compared to the old optimization framework in JModelica.org in regards to computation time and solution obtained through a benchmark on a combined cycle power plant. The results show that the new framework obtains the same solution as the old framework, but in less than half the time.
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
Proceedings of the 11th International Modelica Conference 2015
pages
301 - 310
publisher
Linköping University Electronic Press, Linköping, Sweden
conference name
11th International Modelica Conference
project
LCCC
collocation
language
English
LU publication?
yes
id
201ffac4-54dc-48d7-848a-e618b57753df (old id 8229338)
alternative location
http://www.ep.liu.se/ecp/118/032/ecp15118301.pdf
date added to LUP
2015-11-27 16:05:33
date last changed
2016-05-18 12:57:25
@inproceedings{201ffac4-54dc-48d7-848a-e618b57753df,
  abstract     = {Nonlinear Model Predictive Control (NMPC) is a control strategy based on repeatedly solving an optimal control problem. In this paper we present a new MPC framework for the JModelica.org platform, developed specifically for use in NMPC schemes. The new framework utilizes the fact that the optimal control problem to be solved does not change between solutions, thus decreasing the computation time needed to solve it. The new framework is compared to the old optimization framework in JModelica.org in regards to computation time and solution obtained through a benchmark on a combined cycle power plant. The results show that the new framework obtains the same solution as the old framework, but in less than half the time.},
  author       = {Axelsson, Magdalena and Magnusson, Fredrik and Henningsson, Toivo},
  booktitle    = {Proceedings of the 11th International Modelica Conference 2015},
  language     = {eng},
  pages        = {301--310},
  publisher    = {Linköping University Electronic Press, Linköping, Sweden},
  title        = {A Framework for Nonlinear Model Predictive Control in JModelica.org},
  year         = {2015},
}