Finite-time Convergent Control Barrier Functions with Feasibility Guarantees

TL;DR

This paper introduces a new control barrier function approach that guarantees finite-time convergence to safety sets for nonlinear systems, explicitly considering control bounds and avoiding chattering.

Contribution

It proposes a novel CBF formulation with feasibility guarantees under control constraints, enabling finite-time safety recovery for systems starting outside the safe set.

Findings

Successfully guarantees finite-time convergence to safe set

Ensures feasibility under control bounds

Demonstrates effectiveness in obstacle avoidance case study

Abstract

This paper studies the problem of finite-time convergence to a prescribed safe set for nonlinear systems whose initial states violate the safety constraints. Existing Control Lyapunov-Barrier Functions (CLBFs) can enforce recovery to the safe set but may suffer from the issue of chattering and they do not explicitly consider control bounds. To address these limitations, we propose a new Control Barrier Function (CBF) formulation that guarantees finite-time convergence to the safe set while ensuring feasibility under control constraints. Specifically, we strengthen the initially violated safety constraint by introducing a parameter which enables the exploitation of the asymptotic property of a CBF to converge to the safe set in finite time. Furthermore, the conditions for the existence of such a CBF under control bounds to achieve finite-time convergence are derived via reachability analysis and constraint comparison, providing a systematic approach for parameter design. A case study on 2D obstacle avoidance is presented to demonstrate the effectiveness and advantages of the proposed method.