Path Following Control for Underactuated Airships with Magnitude and Rate Saturation

Sensors

Xiao Guo¹  Jiajun Ou²  Jiace Yuan²  Huabei Gou²  Wenjie Lou³ 

[1] Frontier Institute of Science and Technology Innovation, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;School of Aeronautic Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;School of Electronic and Information Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;

关键词: reinforcement learning;    path following;    underactuated airships;    magnitude and rate saturation;   

DOI  :  10.3390/s20247176

来源: DOAJ

【 摘 要 】

This paper proposes a reinforcement learning (RL) based path following strategy for underactuated airships with magnitude and rate saturation. The Markov decision process (MDP) model for the control problem is established. Then an error bounded line-of-sight (LOS) guidance law is investigated to restrain the state space. Subsequently, a proximal policy optimization (PPO) algorithm is employed to approximate the optimal action policy through trial and error. Since the optimal action policy is generated from the action space, the magnitude and rate saturation can be avoided. The simulation results, involving circular, general, broken-line, and anti-wind path following tasks, demonstrate that the proposed control scheme can transfer to new tasks without adaptation, and possesses satisfying real-time performance and robustness.

【 授权许可】

Unknown