无需先验信息，实现无人机机械臂在未知耦合力下的自适应控制。
Modular Adaptive Aerial Manipulation under Unknown Dynamic Coupling Forces
- 模块化自适应控制，可独立调节飞行器位置、姿态与机械臂的增益。
- 理论证明闭环稳定，实验验证优于现有先进方法。
- 适合需要高鲁棒性空中操作的机器人系统研发者。
成功的空中操作高度依赖控制器对无人机与机械臂间耦合动力学力的有效处理。然而，现有方法或需精确掌握惯性耦合参数，或忽略交互阶段的状态相关不确定性，该问题长期未解。本文提出一种无需任何耦合动态项先验知识的自适应控制方案。与现有方法不同，所提框架具备模块化特性，可分别独立调节飞行器位置、姿态及机械臂子系统的自适应增益。通过解析推导证明了闭环稳定性，并在实时实验中验证了其相较于当前最优方法的有效性。
原文摘要 · Abstract (English)
Successful aerial manipulation largely depends on how effectively a controller can tackle the coupling dynamic forces between the aerial vehicle and the manipulator. However, this control problem has remained largely unsolved as the existing control approaches either require precise knowledge of the aerial vehicle/manipulator inertial couplings, or neglect the state-dependent uncertainties especially arising during the interaction phase. This work proposes an adaptive control solution to overcome this long standing control challenge without any a priori knowledge of the coupling dynamic terms. Additionally, in contrast to the existing adaptive control solutions, the proposed control framework is modular, that is, it allows independent tuning of the adaptive gains for the vehicle position sub-dynamics, the vehicle attitude sub-dynamics, and the manipulator sub-dynamics. Stability of the closed loop under the proposed scheme is derived analytically, and real-time experiments validate the effectiveness of the proposed scheme over the state-of-the-art approaches.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。