@inproceedings{c956f2121db24c1a8f5fff6eb0a7599b,
title = "Attitude synchronization for multiple quadrotors using reinforcement learning",
abstract = "In this paper, a reinforcement learning based control law is proposed to solve the attitude synchronization problem of the leader-following multi-quadrotor systems. The overall system is composed of a team of quadrotors, modeled with highly nonlinear and coupled dynamics. An optimal control solution is obtained by solving an augmented Hamilton-Jacobi-Bellman equation. A reinforcement learning approach is used to learn the optimal control law. Simulation results are provided to verify the effectiveness of the proposed controller.",
author = "Hao Liu and Wanbing Zhao and Lewis, {Frank L.} and Jiang, {Zhong Ping} and Hamidreza Modares",
note = "Publisher Copyright: {\textcopyright} 2019 Technical Committee on Control Theory, Chinese Association of Automation.; 38th Chinese Control Conference, CCC 2019 ; Conference date: 27-07-2019 Through 30-07-2019",
year = "2019",
month = jul,
doi = "10.23919/ChiCC.2019.8865177",
language = "English (US)",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "2480--2483",
editor = "Minyue Fu and Jian Sun",
booktitle = "Proceedings of the 38th Chinese Control Conference, CCC 2019",
}