Trajectory Optimization in Reentry Phase for Hypersonic Gliding Vehicles Using Swarm Intelligence Algorithms

Abstract

The applications of two typical swarm intelligence algorithms in the optimization of the reentry trajectory for the hypersonic gliding vehicles are discussed in our paper. A trajectory optimization strategy based on the swarm intelligence algorithms is presented. Firstly, a penalty function is constructed to deal with the inequality constraint functions. Secondly, the attack angle commands of the vehicles are considered as the parameters to be optimized, and on the basis of the mathematical model of the hypersonic vehicles, the optimal law of the attack angle is considered as the input for the trajectory optimization. Finally, two kinds of swarm intelligence algorithms are applied to handle this difficult optimization problem. Numerical simulations have demonstrated the effectiveness of the swarm intelligence algorithms for the complex and large-scale trajectory optimization problem. Our work lays a solid basis for the schematic trajectory design of the hypersonic gliding vehicles.