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针对敏捷遥感卫星对多个离散观测点在轨自主任务规划问题,在考虑姿态运动方程耦合性的基础上,将问题分解为空间资源调度问题和连续最优控制问题,进而提出了一种结合伪谱法和遗传算法的混合求解算法。该算法针对基于行商问题(TSP)模型建立的空间资源调度问题模型,选用二维编码结构对观测顺序和相对观测时间进行实数编码,并采用遗传算法求解观测序列和观测时间;针对判断观测时间可行性时涉及的时间最优控制问题、以及姿态转移过程中涉及的最小能量消耗问题,将其归结为连续最优控制问题,并基于Gauss伪谱协态变量映射定理,采用Gauss伪谱法进行求解。通过与基于单纯遗传算法的规划算法进行对比试验,本文所提出的基于伪谱法和遗传算法的混合求解策略针对目标问题,在典型工况下姿态转移过程中能量消耗降低60%。
Aiming at the problem of on-orbit autonomous mission planning for multiple discrete observation points by agile remote sensing satellites, the problem is decomposed into the problem of space resource scheduling and the continuous optimal control considering the coupling of attitude motion equations. Then a combinational pseudo- Hybrid Algorithm for Solving Spectral and Genetic Algorithms. The algorithm is based on the TSP model to solve the spatial resource scheduling model. The two-dimensional coding structure is used to encode the observed sequence and relative observation time in real time, and the genetic algorithm is used to solve the observation sequence and observation time. The optimal time control problem involved in sexuality, and the minimum energy consumption involved in the attitude transfer are summarized as continuous optimal control problems, and the Gauss pseudospectral method is used to solve the problem based on the Gauss pseudocolorization covariate mapping theorem . By comparing with the planning algorithm based on simple genetic algorithm, the hybrid solution method proposed in this paper is aimed at the target problem based on the pseudo-spectral method and genetic algorithm, and the energy consumption in the typical case is reduced by 60%.