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Supervisor of Master's Candidates

E-Mail:

Date of Employment:2024-09-05

School/Department:Hangzhou International Innovation Institute

Business Address:Hangzhou international campus, R3 2112

Gender:Male

Status:Employed

Alma Mater:Beihang University

Discipline:Aeronautical and Astronautical Science and Technology
Control Science and Engineering
Transportation Engineering

WANG Mingkai

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Gender:Male

Alma Mater:Beihang University

Paper

Current position: Home / Paper
Reentry Blackout Reachable Set Footprint Prediction Using Multi-Phase Trajectory Optimization

Impact Factor:2.8
DOI number:10.1016/j.asr.2023.05.034
Journal:Advances in Space Research
Key Words:Reusable launch vehicle, Reentry blackout, Reachable set footprint, Trajectory optimization
Abstract:Blackout emerges in the reentry phase of reusable launch vehicles (RLV). Therein, large uncertainties exist in the telemetry signals of RLV, leading to potential safety problems. To facilitate predicting possible ranges of RLV final position when leaving blackout, this paper proposes a modified approach for computing reachable set footprint (RSF). A multi-phase trajectory optimization method is applied to simplified dynamics of RLV. Specifically, partial final boundary conditions are additionally supplemented to the first phase to exploit the intermediate state information during blackout. On this basis, RSF is predicted via solving a series of trajectory optimization problem by sequential convex programming. RSF with additional state information from different altitude are compared in numerical cases. Simulation results show that there exists a suitable range to update RSF using intermediate information. The decision altitude of updating RSF is determined for the exemplary RLV.
Indexed by:Journal paper
First-Level Discipline:Aeronautical and Astronautical Science and Technology
Document Type:J
Volume:72
Issue:6
Page Number:1970-1982
Translation or Not:no
Date of Publication:2023-05-26
Included Journals:SCI
Links to published journals:https://www.sciencedirect.com/science/article/pii/S0273117723003903