|
|
Guidance Law Based on Proximal Policy Optimization |
LI Mengxuan1, GUO Jianguo1, XU Xinpeng2, SHEN Yuheng2 |
1. Institute of Precision Guidance and Control, Northwestern Polytechnical University, Xi’an 710072,
Shaanxi, China;2. Shanghai Electro-Mechanical Engineering Institute, Shanghai 201109, China |
|
|
Abstract The design of guidance law is critical in the interception system. The accuracy of the commonly used variable structure guidance law decreases while intercepting complex manoeuvring targets, and chattering occurs frequently. This paper has proposed a guidance law design method based on near-end strategy optimization. The guidance problem of intercepting manoeuvring targets was abstracted as a Markov decision process, and a reward function evaluating miss distance and line-of-sight angular rate chattering was applied. Comparative experiments show that the interception effect of the guidance law based on near-end strategy optimization and continuous output performs more effectively and can successfully restrain the chattering phenomenon in the sliding mode guidance law, thus providing a significant research prospect and potential application value.
|
Received: 03 July 2023
Published: 09 January 2024
|
|
|
|
|
[1] |
WANG Xu, CAI Yuanli, ZHANG Xuecheng, ZHANG Rongliang, HAN Chenglong. Intercept Guidance Law with a Low Acceleration Ratio Based on Hierarchical Reinforcement Learning[J]. Air & Space Defense, 2024, 7(1): 40-47. |
[2] |
GUO Jianguo, HU Guanjie, XU Xinpeng, LIU Yue, CAO Jin. Reinforcement Learning-Based Target Assignment Method for Many-to-Many Interceptions[J]. Air & Space Defense, 2024, 7(1): 24-31. |
[3] |
MA Chi, ZHANG Guoqun, SUN Junge, LYU Guangzhe, ZHANG Tao. Deep Reinforcement Learning-Based Reconfiguration Method for Integrated Electronic Systems[J]. Air & Space Defense, 2024, 7(1): 63-70. |
[4] |
LIU Xinyu, WANG Sen, ZENG Long, YUAN Shaoheng, HAO Zhenghang, LU Xinyan. An Adaptive Additional Control Strategy for Suppressing Low-Frequency Grid Oscillations in Doubly-Fed Wind Farms[J]. Journal of Shanghai Jiao Tong University, 2023, 57(9): 1156-1164. |
[5] |
LUO Tong, ZHANG Min, LIANG Chengyu. Multi-UAV Cooperative Target Tracking and Guidance Law Design[J]. Air & Space Defense, 2023, 6(3): 113-118. |
[6] |
SUN Jie, LI Zihao, ZHANG Shuyu. Application of Machine Learning in Chemical Synthesis and Characterization[J]. Journal of Shanghai Jiao Tong University, 2023, 57(10): 1231-1244. |
[7] |
YUAN Dongdong (袁冬冬), WANG Yankai∗ (王彦恺). Data Driven Model-Free Adaptive Control Method for
Quadrotor Trajectory Tracking Based on
Improved Sliding Mode Algorithm[J]. J Shanghai Jiaotong Univ Sci, 2022, 27(6): 790-798. |
[8] |
QIN Xuesheng (秦雪升), LIU Yuanhe (刘远贺), LI Kebo (黎克波), LIANG Yangang∗ (梁彦刚). Impact Angle/Time Constraint Guidance Design Based on
Fast Terminal Error Dynamics[J]. J Shanghai Jiaotong Univ Sci, 2022, 27(6): 823-832. |
[9] |
LÜ Qibing (吕其兵), LIU Tianyuan (刘天元), ZHANG Rong (张荣), JIANG Yanan (江亚南), XIAO Lei (肖雷), BAO Jingsong∗ (鲍劲松). Generation Approach of Human-Robot Cooperative Assembly Strategy Based on Transfer Learning[J]. J Shanghai Jiaotong Univ Sci, 2022, 27(5): 602-613. |
[10] |
YU Xinyi (禹鑫燚), WU Jiaxin (吴加鑫), XU Chengjun (许成军), LUO Huizhen (罗惠珍), OU Linlin∗ (欧林林). Adaptive Human-Robot Collaboration Control Based on Optimal Admittance Parameters[J]. J Shanghai Jiaotong Univ Sci, 2022, 27(5): 589-601. |
[11] |
LYU Shuo, ZHANG Qingzhen, GUO Yunhe, FENG Shuo. Attitude Control of Missile with Deflectable Nose Based on Backstepping Sliding Mode Control[J]. Air & Space Defense, 2022, 5(4): 30-37. |
[12] |
SUN Xinglong, MA Kemao, JIANG Yu, HOU Zhenqian. Interception Strategy Design of High Supersonic Targets in the Near Space[J]. Air & Space Defense, 2022, 5(4): 10-18. |
[13] |
LIU Shuangxi, WANG Yichong, ZHU Mengjie, LI Yong, YAN Binbin. Research on Differential Game Guidance Law for Intercepting Hypersonic Vehicles with Small Missile-to-Target Speed Ratio[J]. Air & Space Defense, 2022, 5(2): 49-57. |
[14] |
SHANG Xi, YANG Gewen, DAI Shaohuai, JIANG Yilin. Research on Resource Allocation Strategy of One-to-Many Radar Jamming Based on Reinforcement Learning[J]. Air & Space Defense, 2022, 5(1): 94-101. |
[15] |
JI Xiukun (冀秀坤), HAI Jintao (海金涛), LUO Wenguang (罗文广), LIN Cuixia (林翠霞), XIONG Yu(熊 禹), OU Zengkai (殴增开), WEN Jiayan(文家燕). Obstacle Avoidance in Multi-Agent Formation Process Based on Deep Reinforcement Learning[J]. J Shanghai Jiaotong Univ Sci, 2021, 26(5): 680-685. |
|
|
|
|