Robust Control Barrier Functions with Sector-Bounded Uncertainties

Buch, Jyot; Liao, Shih-Chi; Seiler, Peter

doi:10.48550/arxiv.2109.02537

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“…More recently, tunable ISSf-CBF (TISSf-CBF) has been proposed to reduce the conservatism of the ISSf-CBF method due to the worst-case disturbance assumption [9]. In [10] 1 Ersin Das ¸and Richard M. Murray are with the California Institute of Technology, 1200 East California Boulevard, Pasadena, CA 91125 USA ersindas@caltech.edu; murray@cds.caltech.edu and [11] robust CBF approaches have been investigated for uncertain systems to guarantee safety.…”

Section: Introductionmentioning

confidence: 99%

Robust Safe Control Synthesis with Disturbance Observer-Based Control Barrier Functions

Daş

Murray

2022

2022 IEEE 61st Conference on Decision and Control (CDC)

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In a complex real-time operating environment, external disturbances and uncertainties adversely affect the safety, stability, and performance of dynamical systems. This paper presents a robust stabilizing safety-critical controller synthesis framework with control Lyapunov functions (CLFs) and control barrier functions (CBFs) in the presence of disturbance. A highgain input observer method is adapted to estimate the timevarying unmodelled dynamics of the CBF with an error bound using the first-order time derivative of the CBF. This approach leads to an easily tunable low-order disturbance estimator structure with a design parameter as it utilizes only the CBF constraint. The estimated unknown input and associated error bound are used to ensure robust safety and exponential stability by formulating a CLF-CBF quadratic program. The proposed method is applicable to both relative degree one and higher relative degree CBF constraints. The efficacy of the proposed approach is demonstrated using a numerical simulations of an adaptive cruise control system and a Segway platform with an external disturbance.

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Section: Introductionmentioning

confidence: 99%