航空兵器2024，Vol.31Issue(1)：77-88,12.DOI:10.12132/ISSN.1673-5048.2023.0135
基于深度强化学习的尾旋改出技术
Aircraft Spin Recovery Technique Based on Deep Reinforcement Learning
摘要
Abstract
This paper builds an aircraft simulation environment,and establishes a test model of an automated spin recovery algorithm based on proximal policy optimization(PPO)algorithm.Four kinds of network structures are de-signed,that are basis single stage,basis double stage,deep single stage and deep double stage,to explore the influ-ence of network structure and recovery stage on spin recovery effect.A robustness test experiment is set up,and the al-gorithm is tested and the results are analyzed from the aspects of delay,error and height.关键词
尾旋改出/深度学习/强化学习/近端策略优化/算法测试/飞机Key words
spin recovery/deep learning/reinforcement learning/proximal policy optimization/algorithm test/aircraft分类
军事科技引用本文复制引用
谭健美,王君秋..基于深度强化学习的尾旋改出技术[J].航空兵器,2024,31(1):77-88,12.
