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Dynamic Parametric Sensitivity Optimization Using Simultaneous Discretization in JModelica.org

Magnusson, Fredrik LU ; Palmer, Kyle; Han, Lu and Bollas, George (2015) 2015 International Conference on Complex Systems Engineering In 2015 International Conference on Complex Systems Engineering p.37-42
Abstract
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.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
2015 International Conference on Complex Systems Engineering
pages
37 - 42
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
2015 International Conference on Complex Systems Engineering
external identifiers
  • Scopus:84963699501
ISBN
9781467371797
DOI
10.1109/ComplexSys.2015.7385980
project
LCCC
collocation
language
English
LU publication?
yes
id
a7675587-d305-40b8-8ae2-a13fc5353e8f (old id 8229352)
date added to LUP
2015-12-04 09:08:21
date last changed
2016-10-13 05:08:36
@misc{a7675587-d305-40b8-8ae2-a13fc5353e8f,
  abstract     = {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.<br/><br>
<br/><br>
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.},
  author       = {Magnusson, Fredrik and Palmer, Kyle and Han, Lu and Bollas, George},
  isbn         = {9781467371797},
  language     = {eng},
  pages        = {37--42},
  publisher    = {ARRAY(0x8cacfe8)},
  series       = {2015 International Conference on Complex Systems Engineering},
  title        = {Dynamic Parametric Sensitivity Optimization Using Simultaneous Discretization in JModelica.org},
  url          = {http://dx.doi.org/10.1109/ComplexSys.2015.7385980},
  year         = {2015},
}