Cooperative formation control of fixed-wing UAVs based on deep reinforcement learning

Keyuan Yue; Jianquan Yuan; Mingrui Hao

doi:10.1117/12.2616103

15 February 2022 Cooperative formation control of fixed-wing UAVs based on deep reinforcement learning

Keyuan Yue, Jianquan Yuan, Mingrui Hao

Proceedings Volume 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021); 1216634 (2022) https://doi.org/10.1117/12.2616103
Event: Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 2021, Hong Kong, Hong Kong

Abstract

In recent years, artificial intelligence has attracted research interest and developed rapidly. As one of its representative technologies, deep reinforcement learning methods have gradually combined with various fields to develop numerous research results. Aiming at the motion constraints of fixed-wing aircraft and the existence of disturbances, model uncertainties, etc., this paper designs a fixed-wing aircraft formation controller based on the PID control structure and using the Proximal Policy Optimization algorithm (PPO). The simulation results show that the PID parameters change adaptively with the state of the system, and the system can quickly form the desired formation.

Citation Download Citation

Keyuan Yue, Jianquan Yuan, and Mingrui Hao "Cooperative formation control of fixed-wing UAVs based on deep reinforcement learning", Proc. SPIE 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 1216634 (15 February 2022); https://doi.org/10.1117/12.2616103

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