Disturbance-Robust Backup Control Barrier Functions: Safety Under Uncertain Dynamics

TL;DR

This paper introduces a novel disturbance-robust backup control barrier function framework that guarantees safety for nonlinear systems under unmodeled disturbances by computing a forward invariant set online.

Contribution

It develops a new method to ensure safety in disturbed systems using bounds on system flow, extending backup control barrier functions to uncertain dynamics.

Findings

Successfully guarantees safety in simulations of a double integrator.

Demonstrates effectiveness on a spacecraft rotation problem.

Provides a computationally tractable safety assurance method.

Abstract

Obtaining a controlled invariant set is crucial for safety-critical control with control barrier functions (CBFs) but is non-trivial for complex nonlinear systems and constraints. Backup control barrier functions allow such sets to be constructed online in a computationally tractable manner by examining the evolution (or flow) of the system under a known backup control law. However, for systems with unmodeled disturbances, this flow cannot be directly computed, making the current methods inadequate for assuring safety in these scenarios. To address this gap, we leverage bounds on the nominal and disturbed flow to compute a forward invariant set online by ensuring safety of an expanding norm ball tube centered around the nominal system evolution. We prove that this set results in robust control constraints which guarantee safety of the disturbed system via our Disturbance-Robust Backup Control Barrier Function (DR-bCBF) solution. The efficacy of the proposed framework is demonstrated in simulation, applied to a double integrator problem and a rigid body spacecraft rotation problem with rate constraints.