论文标题
机会限制通过控制屏障功能的稳健控制
Chance Constraint Robust Control with Control Barrier Functions
论文作者
论文摘要
在本文中，我们提出了一种新的方法，可以使用嘈杂的测量和凸细胞分解来合成在多边形环境中导航的线性反馈控制器。我们的方法是基于对收敛和避免碰撞条件的偶然限制的制定。特别是，稳定性和安全保证分别来自机会控制障碍功能（CBF）的约束和偶然控制lyapunov功能（CLF）约束。我们使用凸出过度ximation来获得约束的上限，从而导致凸强性二次程序用于查找控制器。我们应用并为平衡控制和路径控制提供模拟结果。结果表明，控制器对噪声输入很健壮。
In this paper, we propose a novel approach to synthesize linear feedback controllers for navigating in polygonal environments using noisy measurements and a convex cell decomposition. Our method is based on formulating chance constraints for the convergence and collision avoidance condition. In particular, the stability and safety guarantees come from chance Control Barrier Function (CBF) constraints and chance Control Lyapunov Function (CLF) constraints, respectively. We use convex over-approximations to get upper bounds of the constraints, leading to a convex robust quadratic program for finding the controller. We apply and provide simulation results for equilibrium control and path control. The result shows that the controller is robust with the noise input.
