Particle swarm optimization of air-launch vehicle and trajectory
A preliminary design optimization and trajectory optimization of air launch vehicle (ALV) are conducted using particle swarms. The optimization is conducted in three main steps. First, a mission analysis of ALV is performed using the required Delta-V predicted by trajectory optimization. The initia...
| Main Authors: | , , , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/9066/1/ICMAAE-11-162.pdf |
| Summary: | A preliminary design optimization and trajectory optimization of air launch vehicle (ALV) are conducted using particle swarms. The optimization is conducted in three main steps. First, a mission analysis of ALV is
performed using the required Delta-V predicted by trajectory optimization. The initial masses estimated are used for the preliminary ALV design to get the performance and geometric parameters. The second step is to optimize the ALV using particle swarm optimization (PSO) for a
minimum total initial mass. The range of parameters based on existing ALV is used for the design variables. The third step is to optimize the trajectory for maximum payload mass.
It was found that for the selected mission requirements, a maximum payload mass of 203 kg can be carried to a 400-km circular polar orbit using an ALV with minimum total initial
mass of 16,453.9 kg. |
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