1. Efficient worst-case analysis of electronic networks in intervals of frequency
- Author
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Ferber De Vieira Lessa, Moises, Korniienko, Anton, Lofberg, Johan, Morel, Florent, Scorletti, Gérard, Vollaire, Christian, Federal University of Santa Catarina (UFSC), Ampère, Département Méthodes pour l'Ingénierie des Systèmes (MIS), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Electrical Engineering (LIU), Linköping University (LIU), Ampère, Département Energie Electrique (EE), and Fonds de LIA Maxwell
- Subjects
Robustness Analysis ,Convex Optimization ,Worst-case Analysis ,[SPI.NRJ]Engineering Sciences [physics]/Electric power ,Electric Circuits ,Uncertainty ,[SPI.AUTO]Engineering Sciences [physics]/Automatic - Abstract
International audience; This paper presents a new method to compute upper and lower bounds of any voltage or current of an arbitrary linear electric circuit model with uncertain parameters. The bounds are in the frequency domain, and when compared to a previously proposed method, this novel approach provides a higher level of guarantee. The reason is that the bounds are not only computed for a set of fixed frequencies but also computed to a set of intervals of frequencies. The details of the proposed approach, especially the equivalent uncertain element models, are given. Additionally, tests are performed on problems with low and high number of uncertain parameters. Contrary to the classical method of Monte Carlo, the results are not based on a random choice of parameters and do not depend on the number of iterations. It is shown on an example that the classical method of Monte Carlo needs a high number of iterations to reach results in agreement with the proposed method. Then, it leads to higher computation times of several orders of magnitude.
- Published
- 2017
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