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Neymar skips Cleveland trip with Brazil as he continues recovery
Neymar skips Cleveland trip with Brazil as he continues recovery June 4 : Neymar will not travel to Cleveland for Brazil's World Cup warm-up match against Egypt on Saturday as he continues to receive intensive treatment for a calf injury, the Brazilian Football Confederation (CBF) said on Thursday. "Neymar will not travel with the delegation to Cleveland," the CBF said in a statement. "He will remain in New Jersey, undergoing physical therapy and intensifying his physical recovery program."
Where to Put Safety? Control Barrier Function Placement in Networked Control Systems
arXiv:2603.29792v2 Announce Type: replace Abstract: Control barrier functions (CBFs) are widely used to enforce safety in autonomous systems, yet their placement within networked control architectures remains largely unexplored. In this work, we investigate where to enforce safety in a networked control system in which a remote model predictive controller (MPC) communicates with the plant over a delayed network. We compare two safety strategies: i) a local myopic CBF filter applied at the...
Embedding Semantic Risk into Distance Fields and CBFs for Online Monocular Safe Control
Announce Type: new Abstract: We propose an online monocular perception-to-control framework that embeds semantic risk into the distance field used by Control Barrier Function (CBF)-based safe navigation and teleoperation. Many perception-based safety filters assign the same distance-based safety margin to all mapped obstacles or use semantics only as a downstream controller adjustment, rather than encoding semantic risk in the spatial representation. Our framework instead reasons online...
Tunable Real-Time Safety Filters via Set-Based Control Barrier Functions
arXiv:2507.07805v3 Announce Type: replace Abstract: Safety filters for industrial constrained systems are required to combine certified constraint satisfaction, predictable online computation, and a transparent tuning interface. Existing set-based filters are based on a well-established control invariant set design that scales favorably with state and input constraints, but typically intervene only at the set boundary. Control barrier function (CBF)-based filters, by contrast, provide...
Power System CBFs
arXiv:2606.02949v1 Announce Type: new Abstract: Control barrier functions (CBFs) have become a standard tool in safety critical-control systems. CBFs convert state constraints into real time control conditions that certify forward invariance (meaning that once the system starts in a safe region, it remains there for all future times) and minimally modify a nominal controller only when safety is at risk. In power systems, CBF based methods have been proposed for frequency and voltage safety,...
Constricting Tubes for Prescribed-Time Safe Control
arXiv:2603.17003v2 Announce Type: replace-cross Abstract: We propose a constricting Control Barrier Function (CBF) framework for prescribed-time control of control-affine systems with input constraints. Given a system starting outside a target safe set, we construct a time-varying safety tube that shrinks from a relaxed set containing the initial condition to the target set at a user-specified deadline. Any controller rendering this tube forward invariant guarantees prescribed-time recovery...
Robust Koopman Control Barrier Filters for Safe Actor-Critic Reinforcement Learning
arXiv:2605.26452v2 Announce Type: replace Abstract: Safe reinforcement learning (RL) for robotic systems requires policies that improve task performance while satisfying state and input constraints during both training and deployment. Control barrier functions (CBFs) provide a principled mechanism for enforcing forward invariance through minimally invasive safety filters, but their use in model-free RL is limited by the need for accurate dynamics and hand-designed barrier certificates. We...
Brazil lose injured Wesley from World Cup squad, call up Ederson
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Statistical Guarantees in Data-Driven Nonlinear Control: Conformal Robustness for Stability and Safety
arXiv:2506.06228v2 Announce Type: replace Abstract: We present a true-dynamics-agnostic, statistically rigorous framework for establishing exponential stability and safety guarantees of closed-loop, data-driven nonlinear control. Central to our approach is the novel concept of conformal robustness, which robustifies the Lyapunov and zeroing barrier certificates of data-driven dynamical systems against model prediction uncertainties using conformal prediction. It quantifies these...
A model-free approach to control barrier functions for higher-order systems
arXiv:2606.04790v1 Announce Type: new Abstract: Control barrier functions (CBFs) are a widely applied modular tool to ensure safe operation of nonlinear dynamical control systems. However, for their construction accurate knowledge of the system dynamics is typically needed. This requirement was recently alleviated for relative-degree-one systems using techniques from prescribed performance control (PPC) or funnel control (FC).