Robust Adaptive Safety-Critical Control for Unknown Systems with Finite-Time Element-Wise Parameter Estimation

TL;DR

This paper develops a robust adaptive safety-critical control method for unknown systems using control barrier functions and DREM, ensuring safety and finite-time parameter estimation even with noise and disturbances.

Contribution

It introduces a novel element-wise parameter estimation law with DREM that guarantees safety without noise excitation and reduces conservatism in adaptive control.

Findings

Guarantees safety during parameter identification with noisy signals

Achieves finite-time parameter estimation for unknown system parameters

Ensures robustness under bounded disturbances in safety-critical control

Abstract

Safety is always one of the most critical principles for a system to be controlled. This paper investigates a safety-critical control scheme for unknown structured systems by using the control barrier function (CBF) method. Benefited from the dynamic regressor extension and mixing (DREM), an extended element-wise parameter identification law is utilized to dismiss the uncertainty. On the one hand, it is shown that the proposed control scheme can always guarantee the safety in the identification process with noised signal injection excitation, which was not considered in the previous study. On the other hand, the element-wise estimation process in DREM can minimize conservatism of the safe adaptive process compared to other existing adaptive CBF algorithms. The stability as well as the forward invariance of the presented safe control-estimation scheme is proved. Furthermore, the robustness of the scheme under bounded disturbances is analyzed, where a robust CBF with modest conditions is used to ensure safety. The framework is illustrated by simulations on adaptive cruise control, where the slope resistance of the following vehicle is robustly estimated in finite time against small disturbances and the potential crash risk is avoided by the proposed safe control scheme.