www.Autodiff.org - Publication: Automatic Differentiation Applied for Optimization of Dynamical Systems

Automatic Differentiation Applied for Optimization of Dynamical Systems

- Article in a journal -

Area
Dynamical Systems, Electrical Engineering

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

Published in
IEEE Transactions on Magnetics

Year
2010

Abstract
Simulation is ubiquitous in many scientific areas. Applied for dynamic systems usually by employing differential equations, it gives the time evolution of system states. In order to solve such problems, numerical integration algorithms are often required. Automatic differentiation (ad) is introduced as a powerful technique to compute derivatives of functions given in the form of computer programs in a high-level programming language such as FORTRAN, C, or C++. Such technique fits perfectly in combination with gradient-based optimization algorithms, provided that the derivatives are evaluated with no truncation or cancellation error. This paper intends to use ad employed for numerical integration schemes of dynamic systems simulating electromechanical actuators. Then, the resulting derivatives are used for sizing such devices by means of gradient-based constrained optimization.

AD Tools
ADOL-C

BibTeX
@ARTICLE{
         Enciu2010ADA,
       author = "P. Enciu and L. Gerbaud and F. Wurtz",
       journal = "IEEE Transactions on Magnetics",
       title = "Automatic Differentiation Applied for Optimization of Dynamical Systems",
       year = "2010",
       volume = "46",
       number = "8",
       pages = "2943--2946",
       abstract = "Simulation is ubiquitous in many scientific areas. Applied for dynamic systems
         usually by employing differential equations, it gives the time evolution of system states. In order
         to solve such problems, numerical integration algorithms are often required. Automatic
         differentiation (AD) is introduced as a powerful technique to compute derivatives of functions given
         in the form of computer programs in a high-level programming language such as FORTRAN, C, or C++.
         Such technique fits perfectly in combination with gradient-based optimization algorithms, provided
         that the derivatives are evaluated with no truncation or cancellation error. This paper intends to
         use AD employed for numerical integration schemes of dynamic systems simulating electromechanical
         actuators. Then, the resulting derivatives are used for sizing such devices by means of
         gradient-based constrained optimization.",
       keywords = "C++ language;FORTRAN;differential equations;differentiation;gradient
         methods;integration;optimisation;piezoelectric actuators;C;C++;FORTRAN;automatic
         differentiation;computer programs;derivatives-of-functions;differential equations;dynamical
         systems;electromechanical actuators;gradient-based optimization algorithms;high-level programming
         language;numerical integration algorithms;Actuators;Computational modeling;Computer errors;Computer
         languages;Constraint optimization;Cost function;Delay;Design optimization;Differential
         equations;Pervasive computing;Automatic differentiation (AD);dynamic systems;gradient constrained
         optimization",
       doi = "10.1109/TMAG.2010.2044770",
       issn = "0018-9464",
       ad_area = "Dynamical Systems, Electrical Engineering",
       ad_tools = "ADOL-C"
}

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