Optimizing RLV ascent trajectory using PSO algorithms

RLV (reusable launch vehicle) ascent-trajectory optimization is a difficult problem due to the complexity of many physical constraints and optimization cost surfaces. In this paper, a heuristic technique based on a PSO (particle swarm optimization) algorithm is used. The highly constrained nonlinear trajectory planning problem is decomposed into control parameters search problems, The algorithm is able to generate a complete and feasible ascent trajectory, given the ascent conditions, values of constraint parameters, and final conditions. Numerical simulation with a RLV model for ascent mission is presented to demonstrate the capability and effectiveness of the algorithm.