基于改进遗传算法的敏捷卫星姿态路径规划  

Attitude Path Planning for Agile Satellite Based on Improved Genetic Algorithm

作　　者：刘富钰[1,2,3] 崔培玲[1,2,3] 

机构地区：[1]北京航空航天大学仪器科学与光电工程学院,北京100191 [2]惯性技术国家级重点实验室,北京100191 [3]新型惯性仪表与导航系统技术国防重点学科实验室,北京100191

出　　处：《电光与控制》2012年第12期23-28,33,共7页Electronics Optics & Control

基　　金：国家"九七三"项目(2009CB72400101C);国家民用航天预研项目;国家自然基金创新群体(61121003)

摘　　要：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。An improved genetic algorithm was proposed to solve the trajectory planning problem for agile satellite using Double Gimbal Control Moment Gyros （DGCMG） as actuator. Considering the characteristics of rapid attitude maneuver of the agile satellite, a heuristic method was utilized to produce the initial population. Then, in order to guarantee the DGCMG away from the singularity state, an evaluation function was defined based on the energy consumed by DGCMG. Moreover, to satisfy the smooth requirements of the first derivative and second derivative of attitude path, the smooth mutation operator for the angular velocity and the angular acceleration was presented. The simulation results indicated that, under a variety of constraints, such as the control input bounded, actuator saturation, singularity measurement constraint and so on, the attitude path planning by the improved genetic algorithm can meet the maneuvering capability requirement and the energy is more optimal.

关 键 词：敏捷卫星 姿态机动 DGCMG 路径规划 

分 类 号：V448.22[航空宇航科学与技术—飞行器设计]