RT Journal Article
T1 Performance of Gradient-Based Solutions versus Genetic Algorithms in the Correlation of Thermal Mathematical Models of Spacecrafts
A1 Anglada, Eva
A1 Martinez-Jimenez, Laura
A1 Garmendia, Iñaki
AB The correlation of the thermal mathematical models (TMMs) of spacecrafts with the results of the thermal test is a demanding task in terms of time and effort. Theoretically, it can be automatized by means of optimization techniques, although this is a challenging task. Previous studies have shown the ability of genetic algorithms to perform this task in several cases, although some limitations have been detected. In addition, gradient-based methods, although also presenting some limitations, have provided good solutions in other technical fields. For this reason, the performance of genetic algorithms and gradient-based methods in the correlation of TMMs is discussed in this paper to compare the pros and cons of them. The case of study used in the comparison is a real space instrument flown on board the International Space Station.
SN 1687-5966
YR 2017
FD 2017-05-24
LA eng
NO Anglada , E , Martinez-Jimenez , L & Garmendia , I 2017 , ' Performance of Gradient-Based Solutions versus Genetic Algorithms in the Correlation of Thermal Mathematical Models of Spacecrafts ' , International Journal of Aerospace Engineering , vol. 2017 , 7683457 , pp. 1-12 . https://doi.org/10.1155/2017/7683457
NO Publisher Copyright: © 2017 Eva Anglada et al.
DS TECNALIA Publications
RD 1 jul 2024