Safety Critical Control of a System With Element‐Wise Estimation of Unknown Time‐Varying Parameters

ABSTRACT This paper presents a method for guaranteeing the safety of a system with time‐varying parameters. First, we extend Dynamic Regressor Extension and Mixing to estimate time‐varying parameters with a finite‐time update rule, and present a bound on the estimation error. In the case of a constant parameter, we provide an improved lower bound on the update gain compared with the literature. Lastly, the parameter error bound is used to provide a Robust adaptive Control Barrier Function for systems with time‐varying parameters. We conduct a numerical simulation of a system with time‐varying parameters. The presented estimation method estimates the parameters with a smaller mean‐square error compared with methods from the literature. The presented control barrier function can keep the system safe despite parametric uncertainties.

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Publication Details

Journal
International Journal of Robust and Nonlinear Control
Published
2025-08-11
DOI
https://doi.org/10.1002/rnc.70116
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
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article

Safety Critical Control of a System With Element‐Wise Estimation of Unknown Time‐Varying Parameters

Emil Lykke Diget, Yitaek Kim, Christoffer Sloth
International Journal of Robust and Nonlinear Control
Advanced Control Systems Optimization
article

Safety Critical Control of a System With Element‐Wise Estimation of Unknown Time‐Varying Parameters

Emil Lykke Diget, Yitaek Kim, Christoffer Sloth
article en

Abstract

ABSTRACT This paper presents a method for guaranteeing the safety of a system with time‐varying parameters. First, we extend Dynamic Regressor Extension and Mixing to estimate time‐varying parameters with a finite‐time update rule, and present a bound on the estimation error. In the case of a constant parameter, we provide an improved lower bound on the update gain compared with the literature. Lastly, the parameter error bound is used to provide a Robust adaptive Control Barrier Function for systems with time‐varying parameters. We conduct a numerical simulation of a system with time‐varying parameters. The presented estimation method estimates the parameters with a smaller mean‐square error compared with methods from the literature. The presented control barrier function can keep the system safe despite parametric uncertainties.

International Journal of Robust and Nonlinear ControlVol. 36(1)
University of Southern Denmark (DK), Maersk (Denmark) (DK)
Innovationsfonden, EUROfusion, European Commission, Euratom Research and Training Programme
Openalex Percentile: Top 75%
Advanced Control Systems Optimization
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