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. 

Key words: Reentry trajectory optimization, Robust optimization, Uncertainty propagation, Covariance analysis, Describing function