Neural Network Reentry Guidance for Reusable Launch Vehicle Based on Sample Dimensionality Reduction-Reference-Cited by-同舟云学术

Neural Network Reentry Guidance for Reusable Launch Vehicle Based on Sample Dimensionality Reduction

Published:2024-09 Issue:5 Volume:37 Page:
ISSN:0893-1321
Container-title:Journal of Aerospace Engineering
language:en
Short-container-title:J. Aerosp. Eng.

Author:

Xu Qian¹,Xiang Yan²^ORCID,Guo Yang³,Zhang Yufei⁴

Affiliation:

1. Senior Engineer, Beijing Institute of Astronautical System Engineering, No. 1, Donggaodi South St., Fengtai District, Beijing 100076, China.

2. Ph.D. Candidate, School of Aerospace Engineering, Beijing Institute of Technology, No. 5, Zhongguancun South St., Haidian District, Beijing 100081, China; Key Laboratory of Dynamics and Control of Flight Vehicle, Ministry of Education, No. 5, Zhongguancun South St., Haidian District, Beijing 100081, China. ORCID:

3. Engineer, Xi’an Modern Control Technology Research Institute, No. 10, Zhangba East Rd., Yanta District, Xi’an 710065, China (corresponding author).

4. Senior Engineer, Science and Technology on Space Physics Laboratory, No. 1, Donggaodi South St., Fengtai District, Beijing 100076, China.

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JAEEEZ.ASENG-5300

Reference35 articles.

1. Multiconstrained Real-Time Entry Guidance Using Deep Neural Networks

2. Multi-constrained predictor-corrector reentry guidance for hypersonic vehicles

3. Entry Guidance With Terminal Time Control Based on Quasi-Equilibrium Glide Condition

4. Space Shuttle entry guidance performance results

5. Entry trajectory generation without reversal of bank angle

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