Technical Papers
Feb 8, 2020

3D Profile Reconstruction and Guidance for the Terminal Area Energy Management Phase of an Unpowered RLV with Aerosurface Failure

Publication: Journal of Aerospace Engineering
Volume 33, Issue 3

Abstract

This paper focuses on the guidance of an unpowered reusable launch vehicle (RLV) with aerosurface failure in the terminal area energy management (TAEM) phase. The aerosurface failure will limit the bank capability, and has a great influence on the range and turning radius of RLV. To this end, a new TAEM guidance scheme with the ability of online profile reconstruction is proposed in this paper for the bank-constrained RLV. The 3-dimensional (3D) profile is reconstructed online by directly adjusting the parameters of the dynamic pressure profile and the two-external-tangent-circle-based ground track profile. As the coupling between vertical and lateral motion is considered in the trajectory propagation, the reconstruction accuracy is guaranteed. Then, a closed-loop TAEM guidance law is proposed to track the reconstructed 3D profile. The effectiveness and robustness of the guidance scheme are verified by numerical simulations with a variety of initial states and model deviations.

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Acknowledgments

This work was supported by National Natural Science Foundation of China (Grant No. 61803111).

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Go to Journal of Aerospace Engineering
Journal of Aerospace Engineering
Volume 33Issue 3May 2020

History

Received: Sep 12, 2018
Accepted: Sep 16, 2019
Published online: Feb 8, 2020
Published in print: May 1, 2020
Discussion open until: Jul 8, 2020

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Authors

Affiliations

Lecturer, School of Mechanical and Electrical Engineering, Guangzhou Univ., Guangzhou 510006, China. ORCID: https://orcid.org/0000-0003-0938-9879. Email: [email protected]
Engineer, Guangdong Provincial Key Laboratory of Modern Geometric and Mechanical Metrology Technology, Guangdong Institute of Metrology, Guangzhou 510405, China (corresponding author). ORCID: https://orcid.org/0000-0002-8114-1088. Email: [email protected]
Yongji Wang [email protected]
Professor, School of Artificial Intelligence and Automation, Huazhong Univ. of Science and Technology, Wuhan 430074, China. Email: [email protected]

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