Abstract:

Ascent-trajectory optimization of reusable launch vehicles (RLV) is a difficult problem due to the complexity of many physical constraints and optimization cost surfaces. The ascent phase is divided into four segments for trajectory design, which are separation, lifting, power climb and un-power climb. The strategy for each segment trajectory is analyzed according to kinetic characters and the design parameters are studied. For trajectory optimization a heuristic technique based on a particle swarm optimization (PSO) algorithm is used. The highly constrained nonlinear trajectory planning problem is decomposed into design 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.