Adaptive Safety with Control Barrier Functions
Abstract
Adaptive Control Lyapunov Functions (aCLFs) were introduced 20 years ago, and provided a Lyapunov-based methodology for stabilizing systems with parameter uncertainty. The goal of this paper is to revisit this classic formulation in the context of safety-critical control. This will motivate a variant of aCLFs in the context of safety: adaptive Control Barrier Functions (aCBFs). Our proposed approach adaptively achieves safety by keeping the systems state within a safe set even in the presence of parametric model uncertainty. We unify aCLFs and aCBFs into a single control methodology for systems with uncertain parameters in the context of a Quadratic Program (QP) based framework. We validate the ability of this unified framework to achieve stability and safety in an adaptive cruise control (ACC) simulation.
Cite
@article{arxiv.1910.00555,
title = {Adaptive Safety with Control Barrier Functions},
author = {Andrew J. Taylor and Aaron D. Ames},
journal= {arXiv preprint arXiv:1910.00555},
year = {2020}
}
Comments
8 pages, 2 figures, submitted to 2020 IEEE American Control Conference (ACC)