Trajectories optimization of hypersonic vehicle based on a hybrid optimization algorithm of PSO and SQP

We discuss the trajectory optimization problems in the climb segment of the hypersonic vehicle in this paper. First of all, we analyze the hypersonic vehicle model. The strength of the PSO algorithm (Particle Swarm Optimization, PSO) is its strong global optimization ability, but its local optimization ability is relatively weak. The SQP algorithm (Sequential Quadratic Programming, SQP) is quite the opposite, and it has high requirements of the initial trajectory. So we propose a hybrid optimization algorithm of PSO and SQP which combine the advantages of PSO and SQP, while improving the quality of the optimal trajectory.