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基于行为的非合作目标多航天器编队轨迹规划 被引量:9

Trajectory planning for non-cooperative target multi-spacecraft formation based on behavior strategy
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摘要 目前航天器编队轨迹规划的研究并未综合考虑目标非合作性、构型复杂性及控制协同性等问题,针对非合作目标多航天器编队系统,提出了一种基于行为的相对运动轨迹规划方法。首先,基于聚集行为模型设计了期望运动场,将期望速度视为一系列具有不同行为特性的速度矢量和,通过构造平衡态构型公式计算行为调节参数。其次,采用高斯型环境函数描述了非合作目标特性,并通过C-W方程对期望运动场进行了改进,使得该方法在多航天器编队系统与非合作目标形成期望构型的过程中,既能避免编队成员之间发生碰撞,又能保证与非合作目标之间的安全距离。仿真结果表明,该算法可以使多航天器编队系统在3 000s内运动至期望构型。该方法在复杂的、多个控制目标的编队飞行轨迹规划中优势明显,具有自主性、协同性、鲁棒性强等特点,同时可应用于不同类型的编队构型相对运动规划。 The current spacecraft formation trajectory plannings don' t consider noncooperative target, configuration complexity and collaborative control problem. A relative motion trajectory planning method based on behavior strategy was proposed for noncooperative target multi-spacecraft formation system. Firstly, an underlying kinematical field was designed based on the gather model. Expect speed was defined as a series of speed vector with different behavior features. The behavior adjust parameters were calculated by constructing equilibrium shaping formula. Secondly, the non-cooperative target was described with Gauss environment function. The expect kinematical field was improved by using the C-W function. The method not only avoids the collision between the formation members, but also guarantees the safe distance between the non-cooperative targets. The simulation results show that the algorithm can make the multi-spacecraft formation system moving to the expect configuration in 3 000 seconds. The method has obvious advantages when used in complex, multiple control target of the formation system trajectory planning. It is autonomy, collaborative, strong robustness, and etc. At the same time the method can be applied to different types of formation configuration relative motion planning.
出处 《中国空间科学技术》 EI CSCD 北大核心 2017年第1期19-25,共7页 Chinese Space Science and Technology
基金 国家自然科学基金(61473297) 深圳市知识创新计划基础研究项目(JCYJ20140903102802052)
关键词 行为策略 非合作目标 多航天器编队 碰撞规避 轨迹规划 behavior strategy non-cooperative target multi-spacecraft formation collision avoidance trajectory planning
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