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作 者:杨慧婷 王庆辉[1] YANG Huiting;WANG Qinghui(Shenyang University of Chemical Technology,shenyang 110142,China)
机构地区:[1]沈阳化工大学,沈阳110142
出 处:《空间控制技术与应用》2025年第1期75-84,共10页Aerospace Control and Application
基 金:辽宁省教育厅一般资助项目(JYTMS20231500)。
摘 要:针对航天器Lambert双脉冲变轨拦截问题,引入一种自适应模拟退火粒子群(ASAPSO)算法,旨在通过优化两次脉冲的速度增量总和,以实现航天器变轨所需的最小燃料消耗.首先,基于Lambert固定时间飞行定理构建了变轨拦截的数学模型,假设航天器在沿初始轨道飞行一周内机动追逐目标,将两次脉冲变轨的时刻设为决策变量,将燃料消耗量作为适应度函数,并采用ASAPSO混合算法作为优化策略.其次,为了验证ASAPSO算法的有效性,针对同一模型分别采用了传统粒子群算法(PSO)、模拟退火粒子群算法(SAPSO)以及强化学习粒子群算法(RLPSO)进行优化,对比发现ASAPSO算法在较少的迭代次数内就能快速收敛至全局最优解,极大地减少了处理轨道拦截问题的计算量和时间.该算法结合了PSO的全局搜索能力和SA的局部优化特性,为航天器Lambert双脉冲变轨拦截问题提供了一种更为高效、精确的解决方案.An adaptive simulated annealing particle swarm optimization(ASAPSO)algorithm is introduced to solve the problem of Lambert dual-pulse orbital interception,which aims to achieve the minimum fuel consumption by optimizing the sum of the speed increments of the two pulses.First,a mathematical model of orbit change interception is constructed based on Lambert's fixed-time flight theorem.Assuming that the spacecraft maneuvers to pursue the target within one week of its initial orbit flight,the time of two pulse orbit changes is set as the decision variable,the fuel consumption is taken as the fitness function,and the ASAPSO hybrid algorithm is adopted as the optimization strategy.Secondly,in order to verify the effectiveness of ASAPSO algorithm,traditional particle swarm optimization(PSO),simulated annealing particle swarm optimization(SAPSO)and reinforcement learning particle swarm optimization(RLPSO)are used to optimize the same model.The comparison shows that ASAPSO algorithm can quickly converge to the global optimal solution in less iterations,which greatly reduces the computation amount and time to deal with the orbital interception problem.The algorithm combines the global search capability of PSO and the local optimization characteristics of SA to provide a more efficient and accurate solution to the Lambert double pulse orbit change interception problem.
关 键 词:Lambert变轨拦截 粒子群算法 模拟退火算法 参数自适应
分 类 号:V412.4[航空宇航科学与技术—航空宇航推进理论与工程]
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