让四旋翼编队在紧密飞行中自适应调整，应对复杂气流干扰。
Online Adaptation for Flying Quadrotors in Tight Formations
- 基于混合专家学习的自适应控制框架，实时补偿气动干扰。
- 三机编队全程保持垂直对齐，误差小于15厘米。
- 适合需要高精度编队飞行的无人机系统研发人员。
在紧密编队飞行任务中，多架四旋翼无人机因复杂的气动尾流相互作用而面临稳定性挑战。这些气动效应具有高度非线性和快速变化的特点，难以建模和预测。为此，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，使单个四旋翼在编队飞行中能精确跟踪轨迹并实时适应时变气动干扰。我们在两种三机编队配置下进行了评估，结果表明该方法优于多个MPC基线。实验显示，三机编队在整个飞行过程中保持垂直对齐，间距稳定在15厘米以内。结果还表明，当与高精度动力学模型结合时，L1自适应模块对未建模扰动的补偿效果最佳。视频演示及物理实验见：https://youtu.be/9QX1Q5Ut9Rs
原文摘要 · Abstract (English)
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
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