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A Framework for Nonlinear Model Predictive Control in JModelica.org

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Author

  • Magdalena Axelsson
  • Fredrik Magnusson
  • Toivo Henningsson

Summary, in English

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.

Publishing year

2015

Language

English

Pages

301-310

Publication/Series

Proceedings of the 11th International Modelica Conference 2015

Document type

Conference paper

Publisher

Linköping University Electronic Press

Topic

  • Control Engineering

Conference name

11th International Modelica Conference

Conference date

2015-09-21

Conference place

Paris, France

Status

Published

Project

  • LCCC
  • Numerical and Symbolic Algorithms for Dynamic Optimization

Research group

  • LCCC