论文标题
安全至关重要系统的自适应控制障碍功能
Adaptive Control Barrier Functions for Safety-Critical Systems
论文作者
论文摘要
最近的工作表明，通过使用控制屏障函数（CBF）和控制Lyapunov功能，可以将仿射控制系统稳定到所需状态（集合）状态，同时优化二次成本和观察状态和控制约束。在我们自己最近的工作中，我们将高级CBF（HOCBF）定义为具有任意相对程度的系统和约束，以及提高相应QP的可行性的惩罚方法。在本文中，我们引入了自适应CBF（ADACBF），以适应时间变化的控制范围和动态噪声，并解决可行性问题。我们方法的核心是在ADACBF的定义中引入惩罚函数，以及这些惩罚函数的辅助动力学定义是HOCBFS，并被CLF稳定下来。我们通过将其应用于具有不同路面，轮胎滑动和动态噪声的巡航控制问题上，证明了该方法的优势。
Recent work showed that stabilizing affine control systems to desired (sets of) states while optimizing quadratic costs and observing state and control constraints can be reduced to quadratic programs (QP) by using control barrier functions (CBF) and control Lyapunov functions. In our own recent work, we defined high order CBFs (HOCBFs) to accommodating systems and constraints with arbitrary relative degrees, and a penalty method to increase the feasibility of the corresponding QPs. In this paper, we introduce adaptive CBF (AdaCBFs) that can accommodate time-varying control bounds and dynamics noise, and also address the feasibility problem. Central to our approach is the introduction of penalty functions in the definition of an AdaCBF and the definition of auxiliary dynamics for these penalty functions that are HOCBFs and are stabilized by CLFs. We demonstrate the advantages of the proposed method by applying it to a cruise control problem with different road surfaces, tires slipping, and dynamics noise.
