一种基于EPSO的航天器交会轨迹优化方法

Spacecraft Rendezvous Trajectory Optimization Method Based on EPSO

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。

The minimum-fuel, multi-pulse and time-fixed rendezvous problem is investigated, and a population entropy based particle swarm optimization （EPSO） algorithm is proposed to optimize the rendezvous trajectory. The relative motion of two spaeecrafts between two near circular orbits is described by the linearized C-W equations, and taking the minimum energy as a control object, the optimal transfer trajectory based on continuous impulse is got to determine the pulse point location. For the engineering practicability, a multi-pulse control method is used. The location parameters of the pulse point are used to establish the optimization object function of taking the time interval between two pulse-points as the decision variable, and it is solved using the EPSO algorithm. In EPSO, the population entropy is used to describe the particles＇ location confusion degree, and the search space is determined by using the previous population entropy, thus reducing the waste of search space, and improving the searching speed and accuracy of convergence. Simulation results demonstrate the algorithm has better optimization performance, and it is suitable for the spacecraft trajectory optimization.