# Disturbance Observers for Robust Safety-critical Control with Control Barrier Functions

arXiv: https://arxiv.org/abs/2209.08123 · HTML: https://mlsanity.com/paper/2209.08123/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Sep 2022.

## Built on by (most cited first, 3 of 3)

- [Synthesis and Deployment of Maximal Robust Control Barrier Functions through Adversarial Reinforcement Learning](https://mlsanity.com/paper/2604.13192/) (2026)
- [Response-Aware Risk-Constrained Control Barrier Function With Application to Vehicles](https://mlsanity.com/paper/2603.24598/) (2026)
- [Learning Provable Neural Network Observer for Uncertain Dynamical Systems](https://mlsanity.com/paper/2609.30819/) (2026)

## Abstract (arXiv)

This work provides formal safety guarantees for control systems with disturbance. A disturbance observer-based robust safety-critical controller is proposed, that estimates the effect of the disturbance on safety and utilizes this estimate with control barrier functions to attain provably safe dynamic behavior. The observer error bound - which consists of transient and steady-state parts - is quantified, and the system is endowed with robustness against this error via the proposed controller. An adaptive cruise control problem is used as illustrative example through simulations including real disturbance data.