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分布式卫星系统构形调整规划研究
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摘要
利用特定的编队构形实现航天任务目标,是分布式卫星系统(DSS:DistributedSatellite System)的典型特征之一。DSS能够充分发挥现代微小卫星的技术优势,扩大微小卫星应用范围,提高系统的任务可靠性、抗毁性,有效降低航天任务成本。而这些优势的发挥均与DSS的恰当构形和构形调整能力密切相关。因此,构形调整技术成为DSS的关键技术之一。DSS的构形涵盖了位置构形和姿态构形两个方面,构形调整包括构形的捕获、保持、重构与机动。本文主要针对DSS的位置构形调整规划展开深入研究,主要内容与成果如下:
     1.提出了基于多智能体(Multi Agent)协商的DSS构形保持自主规划方法。将DSS中的每个卫星表示为智能体——Agent,每个卫星Agent自主感知自身状态,规划自身的最优调整策略,同时给出调整的效果、代价、意愿等指标,然后各卫星Agent基于这些指标按既定的规则进行协商,来确定最终采用的调整策略。通过仿真分析表明,这种自主分布式规划和整体协同方法能有效处理构形保持规划这一复杂问题。多Agent协商为DSS的自主规划提供了有益的思路。
     2.从单星调整到多星调整逐步深入地展开了DSS多冲量构形最优调整研究。对于单星构形调整问题,重点讨论了复杂期望构形约束的表达和处理,通过算例详细分析了不同优化方法和约束处理方式的适用性和优缺点,提出结合进化算法全局搜索优势和非线性规划的强局部搜索能力解决该问题的综合优化方法。对于复杂多星多冲量最优构形调整问题,重点考虑多星协同的指标,包括定义了燃料不平衡性降低系数,考虑了目标星位分配问题、碰撞避免问题和时间约束等,并采用提出的综合优化方法对示例问题进行了优化求解,得到了全局最优性和局部约束满足性能都很好的解,同时表明了建立的指标模型和提出的约束处理方法的有效性。
     3.提出了DSS构形调整的分布式协同规划方法,将DSS构形最优调整问题划分为两层规划问题,即整体协同的星位分配与首星位相位优化的顶层规划和各星燃料最优调整的底层规划,通过响应面法实现顶层规划和底层规划之间的耦合及各卫星底层规划间的协同。顶层规划基于各卫星底层规划建立的响应面模型开展,然后在顶层规划的优化解附近增加抽样点并由底层规划优化求解,以获得更高精度的响应面模型,再基于新的响应面模型作顶层规划。这种重点探索有价值区域的迭代求解方式,在保证求解精度的同时,可大大节省计算开销。示例问题显示,分布式协同规划方法有效降低了问题求解复杂度和计算代价,明显提高了搜索效果。并且进一步通过各卫星自身优化子问题的并行执行,能够大大缩短求解时间。这为充分利用星上计算资源实现自主规划提供了有价值的技术途径。
     4.采用分析力学方法研究DSS卫星间的相对运动,讨论了DSS相对运动的Hamilton力学建模与生成函数近似求解方法,分析了相对运动的Hamilton函数近似阶数对求解精度的影响。该方法的重要优势在于它能非常自然地适应椭圆轨道和考虑高阶摄动因素,而这些正是当前主流的牛顿力学方法(如Hill方程)研究DSS相对运动的技术瓶颈。通过圆参考轨道和椭圆参考轨道的两种DSS卫星相对运动构形调整算例检验了分析力学建模与求解方法的有效性。
     5.基于考虑J_2项的DSS相对运动Hamilton力学模型和生成函数方法研究了DSS构形调整的最优控制问题,提出了求解最优控制两点边值问题的相对运动生成函数近似迭代方法。首先以较低的计算代价,获得最优控制Hamilton系统生成函数的低阶近似,得到一条近似的最优轨线,然后将最优控制Hamilton系统相对于近似最优轨线求“相对运动”,该“相对运动”仍具有Hamilton性质,利用这一“相对运动”的生成函数低阶近似,可以对近似最优轨线进行迭代修正,从而以计算代价较小的低阶近似逼近计算代价高得多的高阶近似的精度。对圆参考轨道和椭圆参考轨道下的两种DSS构形调整最优控制问题的求解表明该方法达到了较高的控制精度。
     6.面向DSS对仿真验证的需求,提出了基于发布—订阅模式和数据分发服务的DSS运行仿真软件框架的设计方案,不仅支持进程间模型组件的互操作性和可重用性,而且支持进程内部模型组件的互操作性和可重用性,对同时包含强耦合和弱耦合模型、实时性要求随开发进程而不断提高的DSS运行仿真提供灵活支持。在设计的仿真软件框架基础上,部分实现了DSS动力学与控制仿真系统,并通过仿真验证了提出的高精度构形调整最优控制方法的有效性。
Utilizing given formation to accomplish mission goal is a representative characteristics of Distributed Satellite System (DSS). DSS takes good technical advantage of modern micro satellites, extends their applying area, increases mission reliability and damage resistibility, and decreases mission cost effectively, while these advantages of DSS are tightly correlated to proper formation and formation adjusting ability, so formation adjusting is one of the key technique of DSS. Formation of DSS includes position formation and attitude formation, and formation adjusting includes formation initialization, formation keeping, formation reconfiguration and formation maneuver. In this thesis, systematic research on formation adjusting planning was conduct, main contents and accomplishments are as follows:
     1. Autonomous formation keeping planning method based on multi agent negotiation was proposed. Each satellite was mapped to an Agent, which autonomously percept its relative motion state and planned its own adjusting strategy, meanwhile put forward the effect, cost and inclination for its optimal adjustment. Then negotiation was conducted based on these criteria and given rules, such the adjusting strategy was selected. Simulation indicates that this mechanism of autonomous distributed planning and coordination accomplishes relative formation keeping task well, and multi agent negotiation provides a promising way for DSS autonomous formation planning.
     2. Multi-impulse adjusting problem of DSS was systematically investigated from single satellite adjusting to multiple satellite adjusting. For single satellite adjusting, expression and handling of the complex expected formation constraint were discussed. Advantages and disadvantages of different optimization methods and constraint handling methods were analyzed through examples. After that, an integrated way of combining to global search ability of evolutionary algorithm and local search ability of traditional method was proposed. For complex multiple satellite adjusting, indexes of multiple satellite co-ordination were mainly discussed, including fuel inequality, target location assignment, collision avoidance and time constraint. Solving example problems, the integrated methods get excellent results in both global optimal and local constraint satisfaction, which shows the effectiveness of proposed indexes and methods.
     3. Distributed collaborate planning method for DSS formation adjusting was put forward. Formation adjusting problem was divided into two layers planning, i.e. collaborating top planning with satellite location assignment and first satellite phase optimization, and bottom planning with single satellite fuel optimal adjusting. The coordination of multiple satellite bottom planning and the coupling of top and bottom planning were represented by response surface models (RSM). Top planning was conducted based on RSM built by bottom planning, then more samplings were computed by bottom planning around solution of top planning to built more accurate RSM, and new top planning was conducted. That iterative planning searches valuable region with high priority, thus saves computation greatly meanwhile ensures solution precision. Examples show that the method effectively reduces problem solving complexity and computing cost, and evidently improves searching result. By parallel execution of single satellite sub optimization, more computing time will be saved. This provides a valuable way for autonomous on-board planning.
     4. Methods of Analytical Mechanics were used in the relative motion of DSS. Hamilton modeling and generating function method for relative motion were introduced. Approximation of Hamilton function for relative motion of satellite formation and its impact on modeling accuracy were interviewed. Advantages include that these methods adapt to elliptical orbit well, and take high order perturbations naturally, which are bottle necks of traditional methods of Newton Mechanics (such as, Hill's equations). By two adjusting problem of circular reference orbit and elliptic reference orbit respectively, effectiveness of the modeling and solving method was testified.
     5. Optimal control of DSS formation adjusting based on Hamilton Mechanics and generating function method was investigated. An iterative way of solving the two-point boundary value problem induced by optimal control by relative motion generating function approximation was proposed. First low order approximation of generating function and approximate optimal trajectory were obtained. Then using low order approximation of generating function of Hamilton "relative motion" to the approximate optimal trajectory, improvement of the approximate optimal trajectory was iteratively made. In this way, high order approximation accuracy can be obtained by only using low order approximation, which is much cost effective in computing. Solving of a circular reference orbit problem and an elliptical reference orbit problem both reveals that high control precision is reached.
     6. Aiming at the need of DSS simulation, a simulation software framework was designed. It adopt the data distributing service and the publish-subscribe mode. Cooperativity and reusability of both inter-process and inner-process simulation member were considered. So that an environment can be developed uniformly supporting DSS operation simulation, which contains both strong and weak coupling models, and has improving real time simulation requirements along with developing process. Based on the simulation software framework, a simulation system of DSS dynamics and control were partly implemented. And effectiveness of proposed high precision optimal control of DSS formation was testified.
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