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A robust homotopic approach for continuous variable low-thrust trajectory optimization

机译：连续可变低推力轨迹优化的鲁棒同位方法

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This paper presents an improved understanding of the interaction of hybrid optimization method with variable low-thrust trajectory optimization requirements. To analyze fuel-optimal bang-bang control problem, a new version of homotopic algorithm, termed robust homotopic method, is investigated with the prospect of improving the efficiency and automation of the homotopic approach to achieve a high-level of robustness, and consequently enlarge its range of application. Such desired characteristics are promoted via a combination of several techniques. As an effective approach, a modified methodology of the switching detection process is presented for the bang-bang optimal-control problem. Moreover, the value of unknown costates and switching functions are mapped to new normalized intervals throughout the computational process. As a result, the optimal solution is rapidly designed to obtain the global robust-convergence to satisfy all constraints without any ambiguity. The fitting process of all iterations robustly find the unknown variables with the percent of converged solutions to maximum, and the penalty terms are quickly satisfied with predetermined high-accuracy, from the energy-optimal to the fuel-optimal solution, especially close to zero point as a critical point. Accordingly, two advanced interplanetary trajectories are optimized using two dynamic modeling approaches for the instantaneous and constant maximal thrust magnitude as a way to analyze and substantiate the robustness of the proposed algorithm. Results and performances are compared with existing solutions of the same mission problem. (C) 2018 Published by Elsevier Ltd on behalf of COSPAR.
机译：本文提出了对混合优化方法与可变低推力轨迹优化要求之间相互作用的更好的理解。为了分析燃料最优的爆炸控制问题，研究了一种新版本的同位算法，称为鲁棒同位方法，以期提高同位方法的效率和自动化程度，以实现高水平的鲁棒性，并因此扩大规模其应用范围。通过多种技术的组合来促进这种期望的特性。作为一种有效的方法，提出了一种针对开关量最优控制问题的开关检测过程的改进方法。此外，在整个计算过程中，未知的costates和切换函数的值将映射到新的标准化间隔。结果，快速设计了最优解决方案以获得全局鲁棒收敛，从而满足所有约束而没有任何歧义。所有迭代的拟合过程都以收敛解的百分比最大的方式稳健地找到未知变量，并且惩罚项以预定的高精度快速满足，从能量最优解到燃料最优解，尤其是接近零点作为一个关键点。因此，使用两种动态建模方法针对瞬时和恒定最大推力幅值优化了两种先进的行星际轨迹，以此作为分析和证实所提出算法鲁棒性的一种方式。将结果和性能与相同任务问题的现有解决方案进行比较。 （C）2018由Elsevier Ltd代表COSPAR发布。

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