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研究了航天器在固定时间内燃料最省的多脉冲交会问题,提出了一种基于种群熵粒子群优化(Population Entropy based Particle Swarm Optimization,EPSO)算法的交会轨迹优化设计方法。采用线性化C-W方程描述航天器的相对运动,以能耗最优为控制目标,得到了基于连续推力的最优转移轨迹,用于确定脉冲点的位置。考虑工程实用性,采用多脉冲控制方法,利用脉冲点的位置参数建立了以脉冲点时间间隔为决策变量的优化目标函数,并用EPSO算法进行求解。在EPSO中,种群熵描述粒子在搜索空间中位置分布的混乱程度,并通过上一代的种群熵确定下一代的搜索空间,从而减少搜索空间的浪费,提高了算法的搜索速度和收敛精度。仿真结果表明,算法本身具有良好的优化性能,适用于航天器轨迹优化。
In this paper, the most fuel-efficient multi-pulse rendezvous of a spacecraft in a fixed time is studied. A crossover trajectory optimal design method based on Population Entropy-based Particle Swarm Optimization (EPSO) algorithm is proposed. The linearized C-W equation is used to describe the relative movement of the spacecraft. Optimal energy consumption is the target of control. An optimal transfer trajectory based on continuous thrust is obtained and used to determine the position of the pulse point. Considering the practicability of the project, the multi-pulse control method is adopted. The optimal objective function is established based on the position parameters of the pulse point with the decision-making time of the pulse point as the decision variable. The algorithm is solved by the EPSO algorithm. In EPSO, population entropy describes the chaos of particle distribution in search space, and determines the search space of the next generation through the previous generation population entropy, so as to reduce the waste of search space and improve the searching speed and convergence precision of the algorithm. Simulation results show that the algorithm itself has good optimization performance and is suitable for spacecraft trajectory optimization.