Adaptive Safety with Control Barrier Functions and Triggered Batch Least-Squares Identifier

TL;DR

This paper introduces an adaptive safety control method using Control Barrier Functions and a triggered Batch Least-Squares Identifier to handle uncertain systems while ensuring safety and avoiding unbounded estimates.

Contribution

It proposes a novel adaptive control scheme combining a triggered BaLSI with safety constraints, addressing conflicts between control objectives and ensuring bounded estimates.

Findings

Ensures safety via a safety-triggered condition.

Guarantees forward invariance of the safe set.

Demonstrates effectiveness through simulations.

Abstract

In this paper, a triggered Batch Least-Squares Identifier (BaLSI) based adaptive safety control scheme is proposed for uncertain systems with potentially conflicting control objectives and safety constraints. A relaxation term is added to the Quadratic Programs (QP) combining the transformed Control Lyapunov Functions (CLFs) and Control Barrier Functions (CBFs), to mediate the potential conflict. The existing Lyapunov-based adaptive schemes designed to guarantee specific properties of the Lyapunov functions, may grow unboundedly under the effects of the relaxation term. The adaptive law is designed by processing system inputs and outputs, to avoid unbounded estimates and overparameterization problems in the existing results. A safetytriggered condition is presented, based on which the forward invariant property of the safe set is shown and Zeno behavior can be excluded. Simulation results are presented to demonstrate the effectiveness of the proposed adaptive control scheme.