A Framework for Nonlinear Model Predictive Control in JModelica.org

Magdalena Axelsson
Modelon AB, Lund, Sweden

Fredrik Magnusson
Department of Automatic Control, Lund University, Sweden

Toivo Henningsson
Modelon AB, Lund, Sweden

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp15118301

Ingår i: Proceedings of the 11th International Modelica Conference, Versailles, France, September 21-23, 2015

Linköping Electronic Conference Proceedings 118:32, s. 301-310

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Publicerad: 2015-09-18

ISBN: 978-91-7685-955-1

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


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.


Nonlinear Model Predictive Control; JModelica.org; Optimization; IPOPT


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