Zhao Wanbing, Liu Hao, Lewis Frank L, Wang Xinlong
IEEE Trans Cybern. 2022 Aug;52(8):7889-7898. doi: 10.1109/TCYB.2021.3049486. Epub 2022 Jul 19.
In this article, the data-driven optimal formation control problem is addressed for a heterogeneous quadrotor team with a virtual leader. Each quadrotor is considered as a highly nonlinear system with six degrees of freedom and the accurate dynamic information of the quadrotor is difficult to obtain in practical applications. An optimal cascade formation controller, including a position controller and an attitude controller, is proposed to track a virtual leader and form a predesigned formation. By using the reinforcement learning (RL) approach, the optimal formation controller is learned from the quadrotor system data without any knowledge of dynamic information of the quadrotors. Simulation results of a heterogeneous multiquadrotor system in a formation flight are given to show the effectiveness of the proposed controllers.
在本文中，针对具有虚拟领导者的异构四旋翼飞行器团队，研究了数据驱动的最优编队控制问题。每个四旋翼飞行器都被视为一个具有六个自由度的高度非线性系统，并且在实际应用中难以获得四旋翼飞行器的精确动态信息。提出了一种最优级联编队控制器，包括位置控制器和姿态控制器，用于跟踪虚拟领导者并形成预先设计的编队。通过使用强化学习（RL）方法，从四旋翼飞行器系统数据中学习最优编队控制器，而无需任何四旋翼飞行器动态信息的知识。给出了异构多四旋翼飞行器系统编队飞行的仿真结果，以表明所提出控制器的有效性。
