collaborators

11 papers

math.OC2026

Safe Stabilizing Linear Feedback: Necessary and Sufficient Conditions, Optimality, and Margins

Pol Mestres, Shima Sadat Mousavi, Pio Ong +1

Control barrier functions (CBFs) have become an important controller design tool for autonomous systems subject to safety constraints. Despite their popularity, recent works have s…

eess.SY2026

Stability Analysis in Multi-Constraint Safety Filters for Linear Systems

Shima Sadat Mousavi, Pol Mestres, Aaron D. Ames

Multi-constraint safety filters based on control barrier functions for linear systems with affine state constraints yield continuous piecewise-affine closed-loop dynamics and may i…

eess.SY2026

Explicit Control Barrier Function-based Safety Filters and their Resource-Aware Computation

Pol Mestres, Shima Sadat Mousavi, Pio Ong +4

This paper studies the efficient implementation of safety filters that are designed using control barrier functions (CBFs), which minimally modify a nominal controller to render it…

eess.SY2026

Safety Filtering with an Infinite Number of Constraints

Max H. Cohen, Pio Ong, Pol Mestres +1

Control barrier functions (CBFs) provide a rigorous framework for designing controllers enforcing safety constraints. While CBF theory is well-developed for a finite number of safe…

eess.SY2026

Probabilistic Control Barrier Functions for Systems with State Estimation Uncertainty using Sub-Gaussian Concentration

Kazuya Echigo, David E. J. van Wijk, Pol Mestres +3

Safety-critical control systems, such as spacecraft performing proximity operations, must provide formal safety guarantees despite stochastic uncertainties from state estimation an…

eess.SY2026

Structure, Feasibility, and Explicit Safety Filters for Linear Systems

Shima Sadat Mousavi, Max H. Cohen, Pol Mestres +1

Safety filters based on control barrier functions (CBFs) and high-order control barrier functions (HOCBFs) are often implemented through quadratic programs (QPs). In general, espec…