论文标题
充分的条件，可用于使用控制屏障功能的最佳控制问题的可行性
Sufficient Conditions for Feasibility of Optimal Control Problems Using Control Barrier Functions
论文作者
论文摘要
已经表明，可以通过使用控制屏障函数（CBFS）和控制Lyapunov功能（CLFS）将满足的状态和控制限制在优化仿生控制系统的二次成本（一组）融合（一组）收敛。这种方法中的主要挑战之一是确保这些QP的可行性，尤其是在高度相对程度的紧密控制范围和安全限制下。在本文中，我们为可行性提供了足够的条件。足够的条件是由CBF强制执行的单个约束捕获的，该约束将添加到QPS中，以便始终保证其可行性。附加约束的设计始终与现有约束兼容，因此，它不能使一组可行的约束不可行 - 它只能提高整体可行性。我们说明了提议的方法对自适应巡航控制问题的有效性。
It has been shown that satisfying state and control constraints while optimizing quadratic costs subject to desired (sets of) state convergence for affine control systems can be reduced to a sequence of quadratic programs (QPs) by using Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs). One of the main challenges in this approach is ensuring the feasibility of these QPs, especially under tight control bounds and safety constraints of high relative degree. In this paper, we provide sufficient conditions for guranteed feasibility. The sufficient conditions are captured by a single constraint that is enforced by a CBF, which is added to the QPs such that their feasibility is always guaranteed. The additional constraint is designed to be always compatible with the existing constraints, therefore, it cannot make a feasible set of constraints infeasible - it can only increase the overall feasibility. We illustrate the effectiveness of the proposed approach on an adaptive cruise control problem.
