不确定条件下采用协方差描述函数法的再入轨迹鲁棒优化

Translated title of the contribution: Robust Reentry Trajectory Optimization under Uncertainties Using Covariance Analysis Describing Function Technique

Xu Liu, Xiang Li*, Hou Jun Zhang, Yu Heng Guo, Xiao Peng Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Uncertainties are taken into account in reentry trajectory optimization and a robust trajectory optimization model is constructed based on the robust optimization theory. There are computational difficulties in solving this robust trajectory optimization problem due to the random variables associated with the uncertainties. To overcome these difficulties, the covariance analysis describing function technique (CADET) is employed to convert the robust trajectory optimization model into an equivalent deterministic trajectory optimization formulation, which is then solvable by using the existing pseudo-spectral method. In the case study, a robust reentry trajectory optimization problem considering the uncertainties of aerodynamic parameters is solved to obtain the robust optimal trajectories. By comparing with the traditional deterministic optimal trajectories, the robust optimal trajectories are significantly less sensitive to the uncertainties of aerodynamic parameters, showing the effectiveness of the presented method.

Translated title of the contributionRobust Reentry Trajectory Optimization under Uncertainties Using Covariance Analysis Describing Function Technique
Original languageChinese (Traditional)
Pages (from-to)1404-1415
Number of pages12
JournalYuhang Xuebao/Journal of Astronautics
Volume42
Issue number11
DOIs
Publication statusPublished - 30 Nov 2021

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