Auxiliary-Variable Adaptive Control Barrier Functions for Safety Critical Systems

Fuente: arXiv
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Autori principali: Liu, Shuo, Xiao, Wei, Belta, Calin A.
Natura: Preprint
Pubblicazione: 2023
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author Liu, Shuo
Xiao, Wei
Belta, Calin A.
author_facet Liu, Shuo
Xiao, Wei
Belta, Calin A.
contents This paper studies safety guarantees for systems with time-varying control bounds. It has been shown that optimizing quadratic costs subject to state and control constraints can be reduced to a sequence of Quadratic Programs (QPs) using Control Barrier Functions (CBFs). One of the main challenges in this method is that the CBF-based QP could easily become infeasible under tight control bounds, especially when the control bounds are time-varying. The recently proposed adaptive CBFs have addressed such infeasibility issues, but require extensive and non-trivial hyperparameter tuning for the CBF-based QP and may introduce overshooting control near the boundaries of safe sets. To address these issues, we propose a new type of adaptive CBFs called Auxiliary-Variable Adaptive CBFs (AVCBFs). Specifically, we introduce an auxiliary variable that multiplies each CBF itself, and define dynamics for the auxiliary variable to adapt it in constructing the corresponding CBF constraint. In this way, we can improve the feasibility of the CBF-based QP while avoiding extensive parameter tuning with non-overshooting control since the formulation is identical to classical CBF methods. We demonstrate the advantages of using AVCBFs and compare them with existing techniques on an Adaptive Cruise Control (ACC) problem with time-varying control bounds.
format Preprint
id arxiv_https___arxiv_org_abs_2304_00372
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Auxiliary-Variable Adaptive Control Barrier Functions for Safety Critical Systems
Liu, Shuo
Xiao, Wei
Belta, Calin A.
Optimization and Control
Robotics
Systems and Control
Dynamical Systems
This paper studies safety guarantees for systems with time-varying control bounds. It has been shown that optimizing quadratic costs subject to state and control constraints can be reduced to a sequence of Quadratic Programs (QPs) using Control Barrier Functions (CBFs). One of the main challenges in this method is that the CBF-based QP could easily become infeasible under tight control bounds, especially when the control bounds are time-varying. The recently proposed adaptive CBFs have addressed such infeasibility issues, but require extensive and non-trivial hyperparameter tuning for the CBF-based QP and may introduce overshooting control near the boundaries of safe sets. To address these issues, we propose a new type of adaptive CBFs called Auxiliary-Variable Adaptive CBFs (AVCBFs). Specifically, we introduce an auxiliary variable that multiplies each CBF itself, and define dynamics for the auxiliary variable to adapt it in constructing the corresponding CBF constraint. In this way, we can improve the feasibility of the CBF-based QP while avoiding extensive parameter tuning with non-overshooting control since the formulation is identical to classical CBF methods. We demonstrate the advantages of using AVCBFs and compare them with existing techniques on an Adaptive Cruise Control (ACC) problem with time-varying control bounds.
title Auxiliary-Variable Adaptive Control Barrier Functions for Safety Critical Systems
topic Optimization and Control
Robotics
Systems and Control
Dynamical Systems
url https://arxiv.org/abs/2304.00372