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Perturbed Lambert's Problem Solver based on Differential Algebra Optimization

机译:基于差分代数优化的扰动兰伯特问题解决者

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Classical Lambert's problem is an astrodynamical problem implemented in industrial and scientific softwares to solve this specific two-boundary value problem under the hypothesis of a Keplerian dynamic. To design optimal trajectories or to compute initial guess for least-square orbit determination problems, it must be solved and implemented. Earlier works develop numerical and analytical techniques to solve the classical Lambert's problem in the mono-revolution and multi-revolution cases. On the one hand, this results in fast-computing and efficient methods that is employed in state-of-the-art softwares. On the other, the dynamical model is simplistic and the actual final position of the satellite differs of several kilometers once the revolutions number increases. A way to obtain a more close-to-reality solution is to consider a more complete dynamical model by taking into account orbital perturbing forces such as aerodynamic drag and perturbing gravity potential. As previously-introduced algorithms do not consider a perturbed dynamics, this paper develops an optimization algorithm based on the Taylor Differential Algebra to solve the perturbed Lambert's problem. The operations defined in the algebra allow to compute the polynomial approximation of the final state propagation as a function of the initial state to be computed. This polynomial expansion is used to reduce the final position error as in thrust-region optimization. A wide range of numerical simulation is performed in order to have a clear view of the algorithm performances. Test cases have been chosen between the main orbit families (LEO, MEO, GEO, HEO and GTO) in order to have a complete and clear overview of the developed algorithm. Moreover the influence of the polynomial order is studied and a preference expansion order is selected to maximize the performance index. Obtained results are promising and further development are proposed to increment algorithm performances.
机译:古典兰伯特的问题是工业和科学软件中实施的瓦斯科医药问题,在Keplerian动态的假设下解决了这种特定的双边界值问题。为了设计最佳轨迹或计算最初始猜测以进行最小二乘轨道确定问题,必须解决和实施。早期的作品开发了数值和分析技术,以解决古典兰伯特在单革命和多革命案件中的问题。一方面,这导致最新的软件中使用的快速计算和有效的方法。另一方面,一旦转数数量增加,动态模型就是简单的,卫星的实际最终位置几公里的不同。获得更近乎现实解决方案的方法是考虑轨道扰动力,例如空气动力学阻力和扰动潜力,以考虑更完整的动态模型。如前所述的算法不考虑扰动动态,本文开发了基于泰勒差分代数的优化算法来解决扰动兰伯特问题。在代数中定义的操作允许将最终状态传播的多项式近似作为初始状态计算为初始状态。该多项式膨胀用于降低推力区域优化中的最终位置误差。执行广泛的数值模拟,以便具有清晰的算法性能视图。在主轨道家庭(Leo,Meo,Geo,Heo和GTO之间)选择了测试用例,以便完整而明确地概述发达的算法。此外,研究了多项式顺序的影响,并选择偏好膨胀顺序以最大化性能指标。获得的结果是有前途的,提出了增量算法表演的进一步发展。

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