Robust Control Barrier Functions for Safe Control Under Uncertainty Using Extended State Observer and Output Measurement
Jinfeng Chen, Zhiqiang Gao, Qin Lin

TL;DR
This paper introduces a robust safe control method combining extended state observers with control barrier functions, enabling safety guarantees under model uncertainty using only output measurements.
Contribution
It proposes a novel ESO-CBF framework that estimates disturbances and states from outputs, reducing conservativeness and eliminating the need for full state access.
Findings
Less conservative disturbance estimation bounds
Effective safe control under uncertainty demonstrated in simulations
Requires only output measurements for disturbance estimation
Abstract
Control barrier functions-based quadratic programming (CBF-QP) is gaining popularity as an effective controller synthesis tool for safe control. However, the provable safety is established on an accurate dynamic model and access to all states. To address such a limitation, this paper proposes a novel design combining an extended state observer (ESO) with a CBF for safe control of a system with model uncertainty and external disturbances only using output measurement. Our approach provides a less conservative estimation error bound than other disturbance observer-based CBFs. Moreover, only output measurements are needed to estimate the disturbances instead of access to the full state. The bounds of state estimation error and disturbance estimation error are obtained in a unified manner and then used for robust safe control under uncertainty. We validate our approach's efficacy in…
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Taxonomy
TopicsFormal Methods in Verification · Real-Time Systems Scheduling · Real-time simulation and control systems
