Energy-Aware Bayesian Control for Safe Dynamical Systems
Published:Dec 30, 2025 22:24
•1 min read
•ArXiv
Analysis
This paper addresses the critical problem of safe control for dynamical systems, particularly those modeled with Gaussian Processes (GPs). The focus on energy constraints, especially relevant for mechanical and port-Hamiltonian systems, is a significant contribution. The development of Energy-Aware Bayesian Control Barrier Functions (EB-CBFs) provides a novel approach to incorporating probabilistic safety guarantees within a control framework. The use of GP posteriors for the Hamiltonian and vector field is a key innovation, allowing for a more informed and robust safety filter. The numerical simulations on a mass-spring system validate the effectiveness of the proposed method.
Key Takeaways
- •Proposes a novel Bayesian-CBF framework for safe control.
- •Focuses on energy constraints for mechanical and port-Hamiltonian systems.
- •Develops Energy-Aware Bayesian-CBFs (EB-CBFs) using GP posteriors.
- •Provides probabilistic energy safety guarantees.
- •Demonstrates effectiveness through simulations on a mass-spring system.
Reference
“The paper introduces Energy-Aware Bayesian-CBFs (EB-CBFs) that construct conservative energy-based barriers directly from the Hamiltonian and vector-field posteriors, yielding safety filters that minimally modify a nominal controller while providing probabilistic energy safety guarantees.”