Recovery trajectory planning for the reusable launch vehicle

Trajectory planning method for the entire recovery process of the reusable launch vehicle is studied. Firstly, a revised trajectory correction method (RTCM) is proposed to reduce the maximum normal aerodynamic load in the endo-atmosphere unpowered descent phase and improve the vehicle's landing...

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Vydáno v:Aerospace science and technology Ročník 117; s. 106965
Hlavní autoři: Cheng, Guanghui, Jing, Wuxing, Gao, Changsheng
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Masson SAS 01.10.2021
Témata:
Compound trajectory planning method
Particle swarm optimization algorithm
Polynomial guidance law
Reusable launch vehicle
Trajectory correction
Polynomial guidance law
Reusable launch vehicle
Compound trajectory planning method
Trajectory correction
Particle swarm optimization algorithm
ISSN:1270-9638, 1626-3219
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Shrnutí:Trajectory planning method for the entire recovery process of the reusable launch vehicle is studied. Firstly, a revised trajectory correction method (RTCM) is proposed to reduce the maximum normal aerodynamic load in the endo-atmosphere unpowered descent phase and improve the vehicle's landing accuracy on the influence of wind field. It consists of two parts, namely moving the ignition point of the vertical landing phase on the horizontal plane and introducing preset steady wind field into trajectory planning. Secondly, a compound trajectory planning method, which combines Particle Swarm Optimization algorithm (PSO) with Polynomial Guidance Law (PGL), is proposed to complete the optimization task of the entire recovery process. Employing PSO algorithm can avoid the complex calculation of additional angle of attack caused by the preset steady wind field in traditional trajectory correction. To overcome the premature convergence of basic PSO, the traditional re-initialization mechanism is improved. Finally, the guidance simulation of two phases greatly affected by wind is accomplished. The effectiveness of the proposed methods is demonstrated with some scenarios and Monte Carlo simulation.
ISSN:1270-9638
1626-3219
DOI:10.1016/j.ast.2021.106965