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针对可重复使用运载器(RLV)轨迹优化问题,提出了一种混合粒子群法(HPSO).算法采用改进粒子群算法与序列二次规划法相组合的优化方法,应用了一种新的粒子群划分方案,引入调节搜索速度的时变惯性因子,改进了速度和位置的更新策略.给出了上升段轨迹优化问题的飞行运动学方程、发动机模型、气动力模型、约束条件;确定了优化设计步骤,包括配点离散、多邻域改进PSO、HPSO混合策略;并对最小燃料消耗问题进行了优化分析.计算结果表明:HPSO算法在没有合适初始值的情况下,仍能得到满意的全局最优解,具有正确性、高效性和鲁棒性好等优点,可以很好地解决RLV轨迹优化问题.
A hybrid particle swarm optimization (HPSO) algorithm is proposed for the RLV trajectory optimization problem. By using the improved particle swarm optimization algorithm combined with the quadratic programming method, a new particle swarm optimization The time-varying inertia factor which adjusts the searching speed is introduced to improve the updating strategy of velocity and position.The flight kinematics equation, engine model, aerodynamic model and constraints of the ascending section trajectory optimization problem are given, and the optimal design Step, including the discrete-point and multi-neighborhood improvement of PSO and HPSO hybrid strategy, and the optimization of the minimum fuel consumption is analyzed.The results show that the HPSO algorithm can still get a satisfactory global optimum without any suitable initial value Solution, with the advantages of correctness, high efficiency and good robustness, can well solve the RLV trajectory optimization problem.