%0 Journal Article
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%@resumeid 8JMKD3MGP5W/3C9JHN3
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%X In this work a new multi-objective optimization algorithm is presented. The main motivation to develop this new evolutionary algorithm, called M-GEOreal, is to improve the performance and robustness of the M-GEO algorithm previously developed and available in the literature. As a brand new algorithm, several tests have been performed previously with well-known test functions commonly used to verify the performance and robustness of optimization algorithm. In this work the performance and robustness of the M-GEOreal algorithm is investigated in a practical problem, which consist in designing a non-linear control law to control a rigid-flexible satellite attitude. The multi-objective control law requirements are to minimize, simultaneously, the time and the energy during the satellite attitude maneuver. A great advantage of this multi-objective approach is to deal with a set of optimised trade-off creating a region of solutions (non-dominated) available to the designer for posterior choice of an individual solution to be implemented. The non-dominated solutions are represented in the design space (Pareto optimal set) and in the objective functions space (Pareto front). From this design space one gets the best non-linear control law gains to satisfy the performance and robustness requirements of the satellite attitude control system. It is also important to stress that the besides the M-GEOreal be an optimization algorithm it is able to deal with non-linear system, designing a nonlinear control law. From the Pareto Front one obverses that M-GEOreal results are superior to the others two techniques, since its non-control law spend less energy to the same maneuvers time. The better robustness of the M-GEOreal is characterized by the fact that it is able to control a non-linear plant.
%T Design of the Satellite Attitude Control System using  Multi-Objective Generalized  Extremal Optimization
%@electronicmailaddress
%@electronicmailaddress gadelha@dem.inpe.br
%@secondarytype PRE PI
%K optimization algorithm, Nonlinear Optimal Control.
%@usergroup administrator
%@usergroup banon
%@usergroup lattes
%@usergroup secretaria.cpa@dir.inpe.br
%@group
%@group DMC-ETE-INPE-MCT-BR
%@group DMC-ETE-INPE-MCT-BR
%@e-mailaddress gadelha@dem.inpe.br
%3 AAS11 270gad.pdf
%@secondarymark B3_ENGENHARIAS_III
%F lattes: 5801699053436537 2 Mainenti-LopesSouzSous:2011:DeOfTh
%@issn 0065-3438
%2 dpi.inpe.br/plutao/2011/09.22.17.20.58
%@affiliation
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%B Advances in the Astronautical Sciences
%P 1241-1252
%4 dpi.inpe.br/plutao/2011/09.22.17.20.57
%@documentstage not transferred
%D 2011
%V I
%O Setores de Atividade: Atividades profissionais, científicas e técnicas.
%A Mainenti-Lopes, Igor,
%A Souza, Luiz Carlos Gadelha de,
%A Sousa, Fabiano Luis de,
%@dissemination WEBSCI; PORTALCAPES; MGA; COMPENDEX.
%@area ETES