Abstract
A satellite system conceptual design problem is addressed in this work. A multi-objective parametric optimization problem is formulated and efficiently solved. The objectives considered are usually opposed among them, such as performance, mass, budget, and volume. By solving the optimization problem, a minimum set of different satellite configurations is obtained. Therefore, the decision-maker can select the best one, knowing that each one fulfills the requirements suite. The strategy developed in this work is based on the direct numerical simulation (DNS) of the optimization problem. The optimal Pareto front is obtained in a numerical setting. This new tool can optimize the complete system as a whole. Usually, in the standard engineering procedure, each of the interdisciplinary groups performs the optimization of their subsystem. After that, the optimized system is obtained by overlap** all of these individually optimized parts. Clearly, this standard procedure only can create a sub-optimal design. With the approach presented here the global optimal solution is guaranteed. The strategy is applied to a low orbit satellite model and a comparison with a genetic algorithm-based multi-objective optimization procedure is also presented.
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Acknowledgements
This research was partially supported by PID-UTN (Research and Development Program of the National Technological University, Argentina), CONICET (National Council for Scientific and Technical Research, Argentina), and CONAE (National Space Activities Commission, Argentina). The supports of these agencies are gratefully acknowledged.
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Santos, G.J., Giusti, S.M., Alonso, R. (2023). A Pareto Front Numerical Reconstruction Strategy Applied to a Satellite System Conceptual Design. In: Fasano, G., Pintér, J.D. (eds) Modeling and Optimization in Space Engineering. Springer Optimization and Its Applications, vol 200. Springer, Cham. https://doi.org/10.1007/978-3-031-24812-2_12
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