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针对基于双框架控制力矩陀螺(DGCMG)的敏捷卫星姿态快速机动控制问题,提出一种改进的遗传算法进行基于DGCMG的敏捷卫星的姿态路径规划。根据敏捷卫星姿态机动的特点,采用启发式方法生成初始种群,从而提高算法的搜索效率;同时,以DGCMG消耗的能量作为适应度函数,保证DGCMG远离奇异状态;并对星体角速度及其角加速度提出平滑变异算子以保证卫星的星体角速度和指令力矩平滑。仿真结果表明:在控制输入有界、执行机构饱和、奇异测度约束和星体角速度限制等多种约束下,改进的遗传算法能够规划出满足机动能力指标且能量较优的有效路径。
Aimed at the problem of agile satellite attitude fast maneuver control based on dual-frame control moment gyro (DGCMG), an improved genetic algorithm is proposed for attitude path planning of agile satellite based on DGCMG. According to the characteristics of attitude maneuver, the heuristic method is used to generate the initial population to improve the searching efficiency of the algorithm. At the same time, the energy consumed by DGCMG is used as fitness function to ensure that DGCMG is far away from the singular state, and the astral angular acceleration and angular acceleration are smoothed Mutation operator to ensure the satellite’s astral angular velocity and command torque smoothing. Simulation results show that under the constraints of bounded input of control system, saturation of actuator, singularity measure constraint and limit of angular velocity of astral body, the improved genetic algorithm can be used to design an effective path that can meet the maneuverability index and has better energy.