RBCC Mid-section Combined Trajectory Optimization Method Based on Particle Swarm-Pseudospectral Convex Optimization

Abstract

In order to solve the problem of combined trajectory optimization of RBCC mid-section, a nested optimization method based on particle swarm-pseudospectral convex optimization is proposed. Firstly, according to the requirements of the mission, the mid-course flight scheme is given, and the combined trajectory optimization problem is described. Secondly, by analyzing the coupling mechanism of each segment of the combined trajectory, the combined trajectory optimization problem is transformed into the inter-segment convergence static parameter optimization and sub-segment trajectory optimization problem, and a double-layer nested optimization strategy based on particle swarm-pseudospectral convex optimization is designed to solve the problem. The static parameters are determined by the particle swarm optimization algorithm in the upper layer, and on this basis, the pseudospectral convex optimization method is used to optimize the trajectory design in segments, and the non-convex and nonlinear optimization problems are transformed into convex optimization problems by the organic combination of pseudo-spectral discrete method and convex technology, and the sequential convex optimization solution strategy based on trust domain shrinkage is designed, which not only ensures the optimality of each segment of trajectories, but also realizes the rapid solution of the middle segment combined trajectory optimization problem. Finally, the simulation of mid-section combined trajectory optimisation design is completed with an RBCC-powered concept vehicle as an example, which verifies the feasibility and effectiveness of the proposed method.

Keywords

• |rbcc|mid-section combined trajectory|double-layer nesting optimization|particle swarm|pseudospectral convex optimization