A multi-objective optimization of a solar sailcraft trajectory in an Earth-Mars transfer using an evolutionary algorithm
Igor Mainenti-Lopes1; Luiz Carlos Gadelha Souza2; Fabiano Luis DeSousa1
1 Instituto Nacional de Pesquisas Espaciais; 2 Universidade de Brasília
doi:10.20906/CPS/CILAMCE2015-0380
Resumo
The goal of this work was a multi-objective analysis of a solar sailcraft trajectory optimization in an Earth-Mars transfer. Solar sailcraft is propulsion system with great interest in space engineering, since it uses solar radiation to propulsion. So there is no need for propellant to be used, thus it can remains active throughout the entire transfer maneuver. This type of propulsion system opens the possibility to reduce the cost of exploration missions in the solar system. In its simplest configuration, a Flat Solar Sail (FSS) consists of a large and thin structure generally composed by a film fixed to flexible rods. The performance of these vehicles depends largely on the sails attitude relative to the Sun. Using a FSS as propulsion, an Earth-Mars transfer optimization problem was tackled by the M-GEOreal algorithm (Multi-objective Generalized Extremal Optimization with real codification). This algorithm is an Evolutionary Algorithm (AE) based on the theory of Self-Organized Criticality. The FSS was able to perform up to 20 maneuvers until reach the Mars orbit. The M-GEOreal had the task to optimize 21 variables (20 attitude angles e the time between maneuvers) that minimize the transfer time to reach the Mars orbitand the total number of maneuvers necessary to achieve that goal. The M-GEOreal algorithm succeeded to return an optimize frontier for this problem with 5 non-dominated solutions. However, a second attempt to achieve an optimize frontier shown better performance. It consisted in run a SQP algorithm (Sequential quadratic programming) with the M-GEOreal solutions as initial guesses. As result 4 better non-dominated solutions were reached and one of M-GEOreal solution becomes dominated by the new solutions.
Palavras-chave: Solar Sailcraft; Trajectory Optimization; Evolutionary Algorithm; Multi-Objective Optimization; Generalized Extremal Optimization