Derivative-free Parameter Optimization of Functional Mock-up Units

Christian Andersson; Sofia Gedda; Johan Åkesson; Stefan Diehl

Derivative-free Parameter Optimization of Functional Mock-up Units

Christian Andersson, Sofia Gedda, Johan Åkesson, Stefan Diehl

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

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Abstract

Representing a physical system with a mathematical model requires knowledge not only about the physical laws governing the dynamics but also about the parameter values of the system. The parameters can sometimes be measured or calculated, however some of them are often difficult or impossible to obtain in these ways. Finding accurate parameter values is crucial for the accuracy of the mathematical model.

Estimating the parameters using optimization algorithms which attempt to
minimize the error between the response from the mathematical model and the physical system is a common approach for improving the accuracy of the model.

Optimization algorithms usually requires information about the derivatives which may not always be available or not be appropriate for estimation which forces the use of derivative-free optimization algorithms.

In this paper, we present an implementation of derivative-free optimization algorithms for parameter estimation in the JModelica.org platform. The implementation allows the underlying dynamic system to be represented as a Functional Mock-up Unit (FMU), thus enables parameter estimation of models designed in modeling tools following the standardized interface, the Functional Mock-up Interface (FMI), such as Dymola.

Original language	English
Title of host publication	[Host publication title missing]
Publisher	Modelica Association
Publication status	Published - 2012
Event	9th International Modelica Conference - Munich, Germany Duration: 2012 Sept 3 → …

Conference

Conference	9th International Modelica Conference
Country/Territory	Germany
City	Munich
Period	2012/09/03 → …

Bibliographical note

key=and+12mc
project=LCCC-modeling

Subject classification (UKÄ)

Mathematical Sciences
Computational Mathematics

Free keywords

Derivative-free optimization Parameter Estimation JModelica.org FMI Assimulo

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modelica2012_submission_41-3

LCCC
Holmqvist, A. (Researcher), Andersson, N. (Researcher), Cervin, A. (Researcher), Mannesson, A. (Researcher), Gattami, A. (Researcher), Ghulchak, A. (Researcher), Papadopoulos, A. V. (Researcher), Rantzer, A. (Researcher), Robertsson, A. (Researcher), Sootla, A. (Researcher), THEORIN, A. (Researcher), Bernhardsson, B. (Researcher), Olofsson, B. (Researcher), Wittenmark, B. (Researcher), Grussler, C. (Researcher), Johnsson, C. (Researcher), MADJIDIAN, D. (Researcher), Johannesson, E. (Researcher), Magnusson, F. (Researcher), Ståhl, F. (Researcher), Como, G. (Researcher), Chasparis, G. (Researcher), Turesson, G. (Researcher), Dressler, I. (Researcher), Åkesson, J. (Researcher), Cho, J. H. (Researcher), Årzén, K.-E. (Researcher), Åström, K. J. (Researcher), Sou, K. C. (Researcher), Mårtensson, K. (Researcher), Berntorp, K. (Researcher), Soltesz, K. (Researcher), Lessard, L. (Researcher), Hast, M. (Researcher), Rönn, M. (Researcher), Ansbjerg Kjær, M. (Researcher), Maggio, M. (Researcher), Kristalny, M. (Researcher), Garpinger, O. (Researcher), From, P. J. (Researcher), Larsson, P.-O. (Researcher), Giselsson, P. (Researcher), Johansson, R. (Researcher), Hägglund, T. (Researcher), Vladimerou, V. (Researcher), Romero Segovia, V. (Researcher), Aurelius, A. (Researcher), Cedersjö, G. (Researcher), Bür, K. (Researcher), Dellkrantz, M. (Researcher), Du, M. (Researcher), Amani, P. (Researcher), Larsson, R. (Researcher), Tärneberg, W. (Research student), Li, Z. (Researcher), Yin, L. (Researcher), Tufvesson, F. (Researcher), Höst, S. (Researcher), Nilsson, B. (Researcher), Stenström, S. (Researcher), Andersson, J. A. (Researcher), Diehl, S. (Researcher), Dürango, J. (Researcher), Ghazaei Ardakani, M. (Researcher), Forsberg, P.-O. (Researcher), Bengtsson, F. (Researcher), Jörntell, H. (Researcher), Arévalo, C. (Researcher), Führer, C. (Researcher), Andersson, C. (Researcher), Mohammadi, F. (Researcher), Ödling, P. (Researcher), Andersson, M. (Researcher), Kihl, M. (Researcher) & Tunestål, P. (Researcher)
2008/07/01 → 2018/06/30
Project: Research

Cite this

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title = "Derivative-free Parameter Optimization of Functional Mock-up Units",

abstract = "Representing a physical system with a mathematical model requires knowledge not only about the physical laws governing the dynamics but also about the parameter values of the system. The parameters can sometimes be measured or calculated, however some of them are often difficult or impossible to obtain in these ways. Finding accurate parameter values is crucial for the accuracy of the mathematical model. Estimating the parameters using optimization algorithms which attempt to minimize the error between the response from the mathematical model and the physical system is a common approach for improving the accuracy of the model. Optimization algorithms usually requires information about the derivatives which may not always be available or not be appropriate for estimation which forces the use of derivative-free optimization algorithms. In this paper, we present an implementation of derivative-free optimization algorithms for parameter estimation in the JModelica.org platform. The implementation allows the underlying dynamic system to be represented as a Functional Mock-up Unit (FMU), thus enables parameter estimation of models designed in modeling tools following the standardized interface, the Functional Mock-up Interface (FMI), such as Dymola.",

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language = "English",

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AU - Andersson, Christian

AU - Gedda, Sofia

AU - Åkesson, Johan

AU - Diehl, Stefan

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PY - 2012

Y1 - 2012

N2 - Representing a physical system with a mathematical model requires knowledge not only about the physical laws governing the dynamics but also about the parameter values of the system. The parameters can sometimes be measured or calculated, however some of them are often difficult or impossible to obtain in these ways. Finding accurate parameter values is crucial for the accuracy of the mathematical model. Estimating the parameters using optimization algorithms which attempt to minimize the error between the response from the mathematical model and the physical system is a common approach for improving the accuracy of the model. Optimization algorithms usually requires information about the derivatives which may not always be available or not be appropriate for estimation which forces the use of derivative-free optimization algorithms. In this paper, we present an implementation of derivative-free optimization algorithms for parameter estimation in the JModelica.org platform. The implementation allows the underlying dynamic system to be represented as a Functional Mock-up Unit (FMU), thus enables parameter estimation of models designed in modeling tools following the standardized interface, the Functional Mock-up Interface (FMI), such as Dymola.

AB - Representing a physical system with a mathematical model requires knowledge not only about the physical laws governing the dynamics but also about the parameter values of the system. The parameters can sometimes be measured or calculated, however some of them are often difficult or impossible to obtain in these ways. Finding accurate parameter values is crucial for the accuracy of the mathematical model. Estimating the parameters using optimization algorithms which attempt to minimize the error between the response from the mathematical model and the physical system is a common approach for improving the accuracy of the model. Optimization algorithms usually requires information about the derivatives which may not always be available or not be appropriate for estimation which forces the use of derivative-free optimization algorithms. In this paper, we present an implementation of derivative-free optimization algorithms for parameter estimation in the JModelica.org platform. The implementation allows the underlying dynamic system to be represented as a Functional Mock-up Unit (FMU), thus enables parameter estimation of models designed in modeling tools following the standardized interface, the Functional Mock-up Interface (FMI), such as Dymola.

KW - Derivative-free optimization Parameter Estimation JModelica.org FMI Assimulo

M3 - Paper in conference proceeding

BT - [Host publication title missing]

PB - Modelica Association

T2 - 9th International Modelica Conference

Y2 - 3 September 2012

ER -

Derivative-free Parameter Optimization of Functional Mock-up Units

Abstract

Conference

Bibliographical note

Subject classification (UKÄ)

Free keywords

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Projects

LCCC

Cite this