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Warm-Start Multihomotopic Optimization for Low-Thrust Many-Revolution Trajectories

机译:低推力多旋转轨迹的热启动多阶op优化

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Traditionally, fuel-optimal problems for low-thrust spacecraft transfers are connected with energy-optimal problems to increase the convergence possibility of indirect methods. However, for low-thrust many-revolution missions, it is still hard to resolve the energy-optimal problems in a fast and reliable manner due to the strong nonlinearity. To address this issue, a warm-start multihomotopic optimization approach is proposed in this article, wherein the Sundman transformation and multihomotopic techniques are used to connect the energy-optimal problems to linear ones with analytical solutions. This article focuses on the following three contributions. First, the energy-optimal control problems are transformed into true longitude-depended energy-optimal problems based on the homotopy to dynamical model and Sundman transformation, and the equivalence relations of the solutions before and after transformation are obtained analytically. Second, the problems are further connected with time-free energy-optimal problems based on a homotopy to the time constraint. Third, the time-free problems are linearized near a nominal trajectory, and the corresponding analytical solutions are obtained. Starting with the analytical solutions, the algorithm can gradually iterate back to the solutions of the original energy- and fuel-optimal problems. Since the whole transformation process is lossless (optimality is preserved under the transformation process), the developed warm-start multihomotopic algorithm enjoys the advantages on reliable convergence and high computational efficiency. Numerical simulations of Earth-orbit transfer missions from GTO to GEO are conducted by comparing with traditional methods, and the results are given to substantiate the effectiveness of the proposed warm-start multihomotopic method.
机译:传统上,低推力航天器转移的燃料最佳问题与能量最佳问题有关,以提高间接方法的收敛可能性。然而,对于低推力的许多革命任务,由于强烈的非线性,仍然难以以快速可靠的方式解决能源最佳问题。为了解决这个问题,本文提出了一种热启动多阶优化方法,其中Sundman转换和多阶段技术用于将能量最佳问题与分析解决方案的线性溶液连接。本文重点介绍以下三项贡献。首先,能量最优控制问题被转变为真正的经度依赖于统一的能量最佳问题,基于统计的动态模型和Sundman转换,并且在分析地获得转换前后的解决方案的等效关系。其次,基于同型时间约束的同象征,问题进一步与无时间的能量最佳问题相连。第三,无时间问题在标称轨迹附近进行线性化,并且获得了相应的分析解决方案。从分析解决方案开始,该算法可以逐步迭代原始能量和燃料最佳问题的解决方案。由于整个转化过程是无损的(在转换过程中保留最佳状态),所发达的热启动多阶算法始终具有可靠的收敛性和高计算效率的优点。通过与传统方法进行比较,通过比较GTO对Geo的地球轨道转移任务的数值模拟,并给出了所提出的暖起来多主流法的有效性的结果。

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