Kernel software platform for electrical device optimization: Application to the optimization of a linear actuator performance

Amdouni, Imen; Saadaoui, R.; Amraoui, Lilia El; Gillon, F.; Benrejeb, Mohamed; Brochet, P.

doi:10.3233/jae-2011-1386

Cited by 2 publications

(1 citation statement)

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“…In the next section, this problem will be performed using the optimal multiobjective approach, which is developed under O2P platform (Amdouni et al, 2011).…”

Section: Optimization Problem Formulationmentioning

confidence: 99%

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

Amdouni¹,

Amraoui²,

Gillon

et al. 2014

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

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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.

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“…In the next section, this problem will be performed using the optimal multiobjective approach, which is developed under O2P platform (Amdouni et al, 2011).…”

Section: Optimization Problem Formulationmentioning

confidence: 99%