MOON-TO-EARTH TRANSFER TRAJECTORY OPTIMIZATION BASE ON MODIFIED PARTICLE SWARM OPTIMIZATION

Due to large search space and quite a few constraints, the optimization of moon-to-earth transfer trajectory is a challenging problem in lunar return mission. The optimization with multiple constraints is converted to an unconstrained optimization problem with the penalty function method, and a modified particle swarm optimization algorithm is proposed to obtain the optimal moon-to-earth transfer trajectory for the minimum escape velocity increment. A fitness function is used to update the inertia weight, and particle velocity is constrained. Additionally, a random feedback control is applied to the position parameter of particles in a modified algorithm. Furthermore, a convergence performance of the algorithm is analyzed. The optimized result in the lunar return window is verified through the contour map analysis of an objective function.