AD for optimization in electromagnetism applied to semi analytical models combining composed functions

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A Global Optimization Approach Integrating Low Frequency Switching Harmonics Standard for Electric Actuators Design in Aircraft Electrical Networks: Harmonics/Weight Optimization

International audienceIn aircraft applications, ensuring the power quality of the electrical system is one of the critical constraints during network equipment design. This task must be done in accordance with additional constraints like the global weight, cost and volume. In order to prevent high level disturbances in aircraft networks, international standards have fixed the conducted EMI levels that power converters are allowed to emit. On the other hand, respecting these standards at the design step requires analytical and semi-analytical models that are able to achieve a real system analysis and to develop optimized equipments adapted to the network requirements. In this paper we paved the way towards an anticipatory estimation of low frequency harmonics in a typical electrical actuator topology (Filter+Converter+Motor+Reductor). Several models (Three-phase PMW inverter, passive filter, gear reducers and a permanent magnet synchronous machine) were implemented in CADES software in order to find an optimal harmonics/weight Pareto solution using a deterministic or hybrid optimization approach allowing fast optimizations with a high number of parameters and constraints

Dérivation Automatique pour le calcul des sensibilités appliqué au dimensionnement en génie électrique

Sizing by optimization is nowadays of major interest since it provides a fast and reliable way to achieve, with low manufacturing costs, desired performances for products lacking of optimality usually by means of minimizing a cost function. We are particularly interested by constrained gradient based optimization. Such algorithms require accurately valued derivatives of the objective function. This may be the origin of serious problems provided that often such functions may result from complex numerical algorithms. Automatic Dierentiation 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 ts perfectly in combination with gradient based optimization algorithms, provided that the derivatives are valued with no truncation or cancellation error. This work employs Automatic Dierentiation to compute gradients of programs computing the sizing models of electromagnetic devices.Le dimensionnement par optimisation est aujourd'hui d'un intérêt majeur, car il fournit un moyen fiable et rapide en vue de déterminer les performances souhaitées de dispositifs, tout en minimisant une fonction de coût. Nous sommes particulièrement intéressés par l'optimisation sous contraintes basée sur le calcul de gradients. Ces algorithmes nécessitent des valeurs précises des dérivées de la fonction objectif et des performances à contraindre. Evaluer ces dérivées exactes se révèle comme une tâche complexe et très laborieuse, vu que les fonctions de performances et de coûts sont souvent évaluées à partir d'algorithmes numériques complexes. La Dérivation Automatique est une technique efficace pour calculer les dérivées des fonctions décrites au moyen de programmes informatiques dans des langages de programmation de haut niveau tel que Fortran, C ou C + +. Cette technique s'utilise parfaitement pour l'optimisation avec des algorithmes basés sur le calcul de gradients, étant donné que les dérivées sont évaluées sans aucune erreur de troncature ou d'annulation. Ce travail emploie la Dérivation Automatique pour calculer les gradients de programmes de calcul des modèles de dispositifs électromagnétiques

Automatic Differentiation for Sensitivity Calculation in Electromagnetism: Application on Algorithms

International audienc

Automatic Differentiation Applied for Optimization of Dynamical Systems

International audienceAbstract—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 lan- guage such as FORTRAN, C or C++. Such technique fits perfectly in combination with gradient based optimization algorithms, provided that the derivatives are valued with no truncation or cancellation error. This paper intends to use Automatic Differentiation employed for numerical integration schemes of dynamical systems simulating electromechanical actuators. Then, the resulting derivatives are used for sizing such devices by means of gradient based constrained optimization

Automatic Differentiation for Optimization of Dynamical Systems

International audienceSimulation 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

Dérivation automatique pour le calcul des sensibilités appliqué au dimensionnement en génie électrique

Le dimensionnement par optimisation est aujourd'hui d'un intérêt majeur, car il fournit un moyen fiable et rapide en vue de déterminer les performances souhaitées de dispositifs, tout en minimisant une fonction de coût. Nous sommes particulièrement intéressés par l'optimisation sous contraintes basée sur le calcul de gradients. Ces algorithmes nécessitent des valeurs précises des dérivées de la fonction objectif et des performances à contraindre. Evaluer ces dérivées exactes se révèle comme une tâche complexe et très laborieuse, vu que les fonctions de performances et de coûts sont souvent évaluées à partir d'algorithmes numériques complexes. La Dérivation Automatique est une technique efficace pour calculer les dérivées des fonctions décrites au moyen de programmes informatiques dans des langages de programmation de haut niveau tel que Fortran, C ou C + +. Cette technique s'utilise parfaitement pour l'optimisation avec des algorithmes basés sur le calcul de gradients, étant donné que les dérivées sont évaluées sans aucune erreur de troncature ou d'annulation. Ce travail emploie la Dérivation Automatique pour calculer les gradients de programmes de calcul des modèles de dispositifs électromagnétiques.Sizing by optimization is nowadays of major interest since it provides a fast and reliable way to achieve, with low manufacturing costs, desired performances for products lacking of optimality usually by means of minimizing a cost function. We are particularly interested by constrained gradient based optimization. Such algorithms require accurately valued derivatives of the objective function. This may be the origin of serious problems provided that often such functions may result from complex numerical algorithms. Automatic Dierentiation 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 ts perfectly in combination with gradient based optimization algorithms, provided that the derivatives are valued with no truncation or cancellation error. This work employs Automatic Dierentiation to compute gradients of programs computing the sizing models of electromagnetic devices.GRENOBLE1-BU Sciences (384212103) / SudocSudocFranceF

AD applied for the design of electrical devices

6th European Workshop on AD, INRIA Sophia-Antipolis, Franc

Practical use of Automatic Differentiation for Optimization of Electromagnetic Devices

International audienc

Automatic Differentiation for Sensitivity Calculation in Electromagnetism: Application on Algorithms

International audienc