基于多目标遗传算法的太阳高纬探测器轨道设计

Sun Polar Probe Trajectory Design Based on Multi-objective Genetic Algorithm

针对太阳高纬度探测器轨道设计任务要求,研究了基于多目标遗传算法的小推力借力飞行轨道设计方法基于圆锥曲线拼接假设,将探测器轨道分为小推力日心转移轨道段和木星借力飞行轨道段两部分.在日心转移轨道段,选择燃料最省为优化目标,采用标称轨道法设计小推力的推力控制率.在借力飞行轨道段,选择借力后日心轨道倾角为优化目标,对借力飞行的关键参数进行分析.采用多目标遗传算法对该多目标进行了优化.结果表明,多目标遗传算法可以有效地解决轨道设计中的多目标优化问题.优化得到的小推力控制率不仅可以节省发射能量,还可以保证借力飞行后探测器能够进入太阳高纬度探测轨道.

Solar polar probe is of great importance for space physics and the forecast of space weather, but to reach that goal of high solar inclination needs a huge amount of energy. Thus the trajectory of low-thrust and gravity-assist is often used for the sake of energy. In this paper, Jupiter was chosen to be the gravity-assist planet because of its powerful gravitation and the successful experience of Ulysses Probe launched by NASA. Only interplanetary low-thrust transfer stage and gravity-assist stage were considered and linked according to the patched conic approach at the initial design stage, with Earth escape stage being neglected. Low-thrust trajectory was modeled by the so called nominal trajectory concept with linearization about the Kepler orbit, further being analyzed by optimal control using state transmition matrix. In order to reach the goal of high solar inclination, the gravity-assist at Jupiter was modeled and an adjunct angle was defined to confirm the effect of gravity-assist to reach the high solar inclination. MuRi-objective genetic Mgorithm was applied to optimize the two indices being established for energy saving of low-thrust interplanetary transfer and the high solar inclination for the Jupiter gravity-assist. Two optimal schemes were chosen from the final population, whose trajectory parameters are analyzed afterwards. Results showed that multi-objective genetic algorithm was compatible to find promising trajectory scheme of low-thrust gravity-assist trajectory to achieve the demands of solar polar probe mission.