The task of flying in tight formations is challenging for teams of quadrotors because the complex aerodynamic wake interactions can destabilize individual team members as well as the team. Furthermore, these aerodynamic effects are highly nonlinear and fast-paced, making them difficult to model and predict. To overcome these challenges, we present L1 KNODE-DW MPC, an adaptive, mixed expert learning based control framework that allows individual quadrotors to accurately track trajectories while adapting to time-varying aerodynamic interactions during formation flights. We evaluate L1 KNODE-DW MPC in two different three-quadrotor formations and show that it outperforms several MPC baselines. Our results show that the proposed framework is capable of enabling the three-quadrotor team to remain vertically aligned in close proximity throughout the flight. These findings show that the L1 adaptive module compensates for unmodeled disturbances most effectively when paired with an accurate dynamics model. A video showcasing our framework and the physical experiments is available here: https://youtu.be/9QX1Q5Ut9Rs

翻译：四旋翼飞行器团队在紧密编队飞行任务中面临严峻挑战，复杂的空气动力学尾流相互作用不仅会破坏单个成员的稳定性，还会影响整个编队的协同性能。此外，这些空气动力学效应具有高度非线性和快速时变特性，难以精确建模与预测。为应对这些挑战，本文提出L1 KNODE-DW MPC——一种基于混合专家学习的自适应控制框架，使单个四旋翼飞行器能够在编队飞行中精确跟踪轨迹，同时实时适应时变的空气动力学相互作用。我们在两种不同的三机编队构型中评估L1 KNODE-DW MPC，结果表明其性能优于多种MPC基线方法。实验证明，该框架能使三架四旋翼飞行器在整个飞行过程中保持垂直方向的紧密对齐。研究进一步发现，当L1自适应模块与精确动力学模型结合时，能最有效地补偿未建模扰动。展示框架原理与物理实验的视频可通过以下链接获取：https://youtu.be/9QX1Q5Ut9Rs