Publication: Automatic differentiation for electromagnetic models used in optimization
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Automatic differentiation for electromagnetic models used in optimization

- Article in a journal -
 

Area
Electrical Engineering

Author(s)
P. Enciu , F. Wurtz , L. Gerbaud , B. Delinchant

Published in
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

Year
2009

Abstract
Purpose – The purpose of this paper is to illustrate automatic differentiation (ad) as a new technology for the device sizing in electromagnetism by using gradient constrained optimization. Component architecture for the design of engineering systems (CADES) framework, previously described, is presented here with extended features. Design/methodology/approach – The paper is subject to further usage for optimization of ad (also named algorithmic differentiation) which is a powerful technique that computes derivatives of functions described as computer programs in a programming language like C/C++, FORTRAN. Findings – Indeed, analytical modeling is well suited regarding optimization procedure, but the modeling of complex devices needs sometimes numerical formulations. This paper then reviews the concepts implemented in CADES which aim to manage the interactions of analytical and numerical modeling inside of gradient-based optimization procedure. Finally, the paper shows that ad has no limit for the input program complexity, or gradients accuracy, in the context of constrained optimization of an electromagnetic actuator. Originality/value – ad is employed for a large and complex numerical code computing multidimensional integrals of functions. Thus, the paper intends to prove the ad capabilities in the context of electromagnetic device sizing by means of gradient optimization. The code complexity as also as the implications of ad usage may stand as a good reference for the researchers in this field area.

AD Tools
ADOL-C

BibTeX
@ARTICLE{
         Enciu2009Adf,
       author = "P. Enciu and F. Wurtz and L. Gerbaud and B. Delinchant",
       title = "Automatic differentiation for electromagnetic models used in optimization",
       journal = "{COMPEL}: {T}he International Journal for Computation and Mathematics in Electrical
         and Electronic Engineering",
       year = "2009",
       volume = "28",
       number = "5",
       pages = "1313--1326",
       abstract = "Purpose – The purpose of this paper is to illustrate automatic
         differentiation (AD) as a new technology for the device sizing in electromagnetism by using gradient
         constrained optimization. Component architecture for the design of engineering systems (CADES)
         framework, previously described, is presented here with extended features.
         Design/methodology/approach – The paper is subject to further usage for optimization of AD
         (also named algorithmic differentiation) which is a powerful technique that computes derivatives of
         functions described as computer programs in a programming language like C/C++, FORTRAN. Findings
         – Indeed, analytical modeling is well suited regarding optimization procedure, but the
         modeling of complex devices needs sometimes numerical formulations. This paper then reviews the
         concepts implemented in CADES which aim to manage the interactions of analytical and numerical
         modeling inside of gradient-based optimization procedure. Finally, the paper shows that AD has no
         limit for the input program complexity, or gradients accuracy, in the context of constrained
         optimization of an electromagnetic actuator. Originality/value – AD is employed for a
         large and complex numerical code computing multidimensional integrals of functions. Thus, the paper
         intends to prove the AD capabilities in the context of electromagnetic device sizing by means of
         gradient optimization. The code complexity as also as the implications of AD usage may stand as a
         good reference for the researchers in this field area.",
       keywords = "Computer software, Constraint handling, Electromagnetism, Gradient methods,
         Modelling, Optimization techniques",
       doi = "10.1108/03321640910969557",
       ad_area = "Electrical Engineering",
       ad_tools = "ADOL-C"
}


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