High-order Barrier Functions: Robustness, Safety and Performance-Critical Control
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Abstract (arXiv)
In this paper, we propose a notion of high-order (zeroing) barrier functions that generalizes the concept of zeroing barrier functions and guarantees set forward invariance by checking their higher order derivatives. The proposed formulation guarantees asymptotic stability of the forward invariant set, which is highly favorable for robustness with respect to model perturbations. No forward completeness assumption is needed in our setting in contrast to existing high order barrier function methods. For the case of controlled dynamical systems, we relax the requirement of uniform relative degree and propose a singularity-free control scheme that yields a locally Lipschitz control signal and guarantees safety. Furthermore, the proposed formulation accounts for "performance-critical" control: it guarantees that a subset of the forward invariant set will admit any existing, bounded control law, while still ensuring forward invariance of the set. Finally, a non-trivial case study with rigid-body attitude dynamics and interconnected cell regions as the safe region is investigated.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Mar 2021.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 1; 2025: 1; 2026: 2.
7 papers.
- 2022Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approachcited by 6
- 2023A General Framework for Verification and Control of Dynamical Models via Certificate Synthesiscited by 6
- 2026Provably Safe, Yet Scalable Reinforcement Learningcited by 1
- 2023Safe Reinforcement Learning in Tensor Reproducing Kernel Hilbert Spacecited by 0
- 2024Fault Tolerant Neural Control Barrier Functions for Robotic Systems under Sensor Faults and Attackscited by 0
- 2025Safe Learning Control with Optimality and Stability Guaranteescited by 0
- 2026Response-Aware Risk-Constrained Control Barrier Function With Application to Vehiclescited by 0
- 2026Provably Safe, Yet Scalable Reinforcement Learning12 Jun 2026
- 2026Response-Aware Risk-Constrained Control Barrier Function With Application to Vehicles13 Mar 2026
- 2025Safe Learning Control with Optimality and Stability Guarantees26 Jan 2025
- 2024Fault Tolerant Neural Control Barrier Functions for Robotic Systems under Sensor Faults and Attacks28 Feb 2024
- 2023Safe Reinforcement Learning in Tensor Reproducing Kernel Hilbert Space1 Dec 2023
- 2023A General Framework for Verification and Control of Dynamical Models via Certificate Synthesis12 Sep 2023
- 2022Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach3 Aug 2022