Search

Your search keyword '"Amraoui, Lilia EL"' showing total 30 results
Start Over Author "Amraoui, Lilia EL"
30 results on '"Amraoui, Lilia EL"'

13. Optimal control of electrical machines using Pontryagin’s maximum principle.

Author

Bekir, Wissem, Amraoui, Lilia EL, and Gillon, Frédéric

Abstract

This paper presents an optimization method that deal with control techniques for electrical machines, in order to impose a displacement with a minimum of energy consumption. It’s a generic method; However, its application to electrical machines is complex for implementation. The present work provides the shape of the optimal solution. Moreover, a resolution technique related to the nature of the model is proposed, which facilitate the numerical resolution of costate problem. The method is applied to hybrid stepper motor and the obtained results are then analyzed. [ABSTRACT FROM AUTHOR]

Published
2020
Full Text
View/download PDF

30. Multiobjective approach developed for optimizing the dynamic behavior of incremental linear actuators.

Author

Amdouni, Imen, Amraoui, Lilia El, Gillon, Frédéric, Benrejeb, Mohamed, and Brochet, Pascal

Subjects
*ACTUATORS, *MATHEMATICAL optimization, *FINITE element method, *PARALLEL computers, *GENETIC algorithms
Abstract

Purpose – The purpose of this paper is to develop an optimal approach for optimizing the dynamic behavior of incremental linear actuators. Design/methodology/approach – First, a parameterized design model is built. Second, a dynamic model is implemented. This model takes into account the thrust force computed from a finite element model. Finally, the multiobjective optimization approach is applied to the dynamic model to optimize control as well as design parameters. Findings – The Pareto front resulting from the optimization approach (or the parallel optimization approach,) is better than the Pareto, which is obtained from the only application of MultiObjective Genetic Algorithm (MOGA) method (or parallel MOGA with the same number of optimization approach objective function evaluations). The only use of MOGA can reach the region near an optimal Pareto front, but it consumes more computing time than the multiobjective optimization approach. At each flowchart stage, parallelization leads to a significant reduction of computing time which is halved when using two-core machine. Originality/value – In order to solve the multiobjective problem, a hybrid algorithm based on MOGA is developed. [ABSTRACT FROM AUTHOR]

Published
2014
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results