Robust Adaptive Backup Control Barrier Functions

This repository contains the implementation of Robust Adaptive Backup Control Barrier Functions, submitted to IEEE Control Systems Letters (L-CSS), 2026.

Ersin Daş, David E. J. van Wijk, Tamas G. Molnar, Aaron D. Ames, and Joel W. Burdick

Paper: https://arxiv.org/pdf/2607.20842

Prerequisites

• Python 3.9 or later.
• Required Python libraries:
  • numpy
  • scipy
  • jax
  • cvxpy
  • quadprog
  • matplotlib

Contents

The quadrotor folder contains the planar quadrotor example from the paper: the true and estimated dynamics, the DREM parameter estimator, the vanilla and robust adaptive bCBF-QP safety filters, and the scripts used to run the simulation and generate the figure.

• main_sim.py runs a single simulation (vanilla, adaptive, or nominal, see --mode).
• collect_data.py runs all three cases and saves the data used for the paper figure.
• make_fig.py generates the figure from the saved data.

Supplementary material

Supplementary Material.pdf gives the proof that the backup controller keeps the backup set forward invariant (Proposition 1). The same conditions are checked numerically in quadrotor/control.py, in checkValidBackup.