论文标题
在风干扰下，基于安全学习的跟踪控制
Safe Learning-based Tracking Control for Quadrotors under Wind Disturbances
论文作者
论文摘要
在精确的轨迹跟踪上执行安全性对于受风干扰的空中机器人技术至关重要。在本文中，我们提出了基于学习的安全性级联二次编程控制（SPQC），以在风干扰下进行安全轨迹跟踪。 SPQC控制器由位置级控制器和态度级别的控制器组成。高斯工艺（GPS）用于估计风干扰引起的不确定性，然后是标称基于Lyapunov的级联二次程序（QP）控制器来跟踪参考轨迹。为了避免跟踪时，以最小的修改方式在每个名义QP控制器上强制执行以控制障碍功能（CBF）表示的安全限制（CBF）。通过（a）在不同的风干扰下（a）轨迹跟踪的数值验证来说明所提出的SPQC控制器的性能，以及（b）在杂乱无章的环境中轨迹跟踪，在风干扰下具有密集的时变障碍物。
Enforcing safety on precise trajectory tracking is critical for aerial robotics subject to wind disturbances. In this paper, we present a learning-based safety-preserving cascaded quadratic programming control (SPQC) for safe trajectory tracking under wind disturbances. The SPQC controller consists of a position-level controller and an attitude-level controller. Gaussian Processes (GPs) are utilized to estimate the uncertainties caused by wind disturbances, and then a nominal Lyapunov-based cascaded quadratic program (QP) controller is designed to track the reference trajectory. To avoid unexpected obstacles when tracking, safety constraints represented by control barrier functions (CBFs) are enforced on each nominal QP controller in a way of minimal modification. The performance of the proposed SPQC controller is illustrated through numerical validations of (a) trajectory tracking under different wind disturbances, and (b) trajectory tracking in a cluttered environment with a dense time-varying obstacle field under wind disturbances.
