高超声速飞行器再入轨迹多目标优化

针对飞行器再入轨迹多目标优化问题,提出了一种基于粒子群算法与层次分析法的综合求解策略。首先,根据飞行器的动力学模型以及再入约束条件,建立了飞行器多目标优化模型;然后,考虑到粒子群算法只能求解无约束单目标问题,采用罚函数处理飞行过程中的约束条件和优化目标;最后,针对不同约束及目标的权重对再入轨迹的影响,利用层次分析法建立包含主观评估信息的优化模型,采用粒子群算法优化求解满足相应约束条件的再入轨迹问题。仿真结果表明,该方法所生成的优化轨迹具有较高的精度和计算效率,并对设计者的主观需求有良好的体现。

Multi-objective trajectory optimization for hypersonic reentry vehicle

Aiming at the multi-objective trajectory optimization problem for the hypersonic reentry vehicle, a comprehensive strategy combined with the analytic hierarchy process (AHP) and particle swarm optimization (PSO) method is proposed.Firstly, based on the dynamic model and constraints of the vehicle, the multi-objective optimization model is established.Then, the penalty function is adopted to handle the constraints and the objectives due to the PSO can only solve unconstrained single objective problems.Considering the weights of constraints and objectives may have different influence on the optimization results, an optimization model with subjective evaluation information is established via AHP, and the final trajectory is obtained via PSO.Simulation results show that the proposed strategy can generate different optimization trajectories according to various demands of the designers with high precision and efficiency.