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Dynamic Parametric Sensitivity Optimization Using Simultaneous Discretization in JModelica.org

Författare

  • Fredrik Magnusson
  • Kyle Palmer
  • Lu Han
  • George Bollas

Summary, in English

Dynamic optimization problems involving parametric sensitivities, such as optimal experimental design, are typically solved using shooting-based methods, while leveraging numerical integrators with sensitivity computation capabilities. In this paper we present how simultaneous discretization can be employed to solve these problems, by augmenting the dynamic optimization problems with forward sensitivity equations.



We present an implementation of this approach in the open-source, Modelica-based tool JModelica.org, which addresses the need for solving optimal experimental design problems in Modelica tools. The implementation is demonstrated on a fed-batch reactor and a plate-fin heat exchanger.

Publiceringsår

2015

Språk

Engelska

Sidor

37-42

Publikation/Tidskrift/Serie

2015 International Conference on Complex Systems Engineering

Dokumenttyp

Konferensbidrag

Förlag

IEEE - Institute of Electrical and Electronics Engineers Inc.

Ämne

  • Control Engineering

Conference name

2015 International Conference on Complex Systems Engineering

Conference date

2015-11-09

Status

Published

Projekt

  • Numerical and Symbolic Algorithms for Dynamic Optimization
  • LCCC

Forskningsgrupp

  • LCCC

ISBN/ISSN/Övrigt

  • ISBN: 9781467371797