Webbläsaren som du använder stöds inte av denna webbplats. Alla versioner av Internet Explorer stöds inte längre, av oss eller Microsoft (läs mer här: * https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Var god och använd en modern webbläsare för att ta del av denna webbplats, som t.ex. nyaste versioner av Edge, Chrome, Firefox eller Safari osv.

A Framework for Nonlinear Model Predictive Control in JModelica.org

In English

Författare

  • 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.

Publiceringsår

2015

Språk

Engelska

Sidor

301-310

Publikation/Tidskrift/Serie

Proceedings of the 11th International Modelica Conference 2015

Dokumenttyp

Konferensbidrag

Förlag

Linköping University Electronic Press

Ämne

  • Control Engineering

Conference name

11th International Modelica Conference

Conference date

2015-09-21

Conference place

Paris, France

Status

Published

Projekt

  • LCCC
  • Numerical and Symbolic Algorithms for Dynamic Optimization

Forskningsgrupp

  • LCCC