%0 Conference Proceedings
%4 sid.inpe.br/mtc-m16d/2016/07.29.16.36
%2 sid.inpe.br/mtc-m16d/2016/07.29.16.36.48
%@issn 2177-3114
%T Reproducing Amazonia-1 Satellite Thermal Behavior with Artificial Neural Networks
%D 2016
%A Reis Junior, José Daniel,
%A Ambrosio, Ana Maria,
%A Sousa, Fabiano Luis de,
%A Silva, Douglas Felipe da,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress daniel.reis@inpe.br
%E Cerqueira, Christopher Shneider,
%E Souza, Alain Giacobini de,
%E Oliveira Junior, Eloy Martins de,
%E Bertoldo Junior, Jorge,
%E Yassuda, Irineu dos Santos,
%E Lima, Jeanne Samara dos Santos,
%E Morais, Marcelo Henrique Essado de,
%E Oliveira, Mônica Elizabeth Rocha de,
%E Gondo, Suely Mitsuko Hirakawa,
%E Fornari, Celso Israel,
%E Toledo, Rafael Cardoso,
%E Fischer, Gustavo Alexandre Achilles,
%B Workshop em Engenharia e Tecnologias Espaciais, 7 (WETE)
%C São José dos Campos
%8 23-25 ago. 2016
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%K Artificial Satellite, Thermal Control, Real-Time Simulation, Artificial Neural Networks.
%X The Operational Simulator is a software tool designed to support the operation phase of space systems. The thermal model of the Operational Simulator can be very demanding in terms of computational processing, if the simulator aims to be accurate in comparison to the actual spacecraft thermal model. Here we propose the use of Artificial Neural Networks to learn and reproduce the thermal behavior of the Amazonia-1 satellite. The results are very promising and indicate that this approach can be applied, at least for a few scenarios as used in this work.
%9 Engenharia e Gerenciamento de Sistemas Espaciais
%@language en
%3 Artigo WETE 2016 vFinal.doc