Guidance Design for Escape Flight Vehicle Using Evolution Strategy Enhanced Deep Reinforcement Learning-Reference-Cited by-同舟云学术

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Guidance Design for Escape Flight Vehicle Using Evolution Strategy Enhanced Deep Reinforcement Learning

Published:2024 Issue: Volume:12 Page:48210-48222
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Hu Xiao¹,Wang Tianshu¹,Gong Min²^ORCID,Yang Shaoshi³^ORCID

Affiliation:

1. School of Aerospace Engineering, Tsinghua University, Beijing, China

2. China Academy of Launch Vehicle Technology, Beijing, China

3. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China

Funder

Beijing Municipal Natural Science Foundation

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10485410.pdf?arnumber=10485410

Reference37 articles.

1. Guidance based on zero effort miss for super-range exoatmospheric intercept;Chen;Acta Aeronautica et Astronautica Sinica,2009

2. A zero-effort miss distance-based guidance law for endoatmoshperic interceptor;Liu;J. Astronaut.,2010

3. Solving singular two-point boundary value problem in reproducing kernel space

4. A linear quadratic optimal guidance method for lunar soft landing;Huang;Aerosp. Control,2006

5. Design and Analysis of State-Feedback Optimal Strategies for the Differential Game of Active Defense

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