collaborators

6 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

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…

eess.SY2026

Stability Margins of CBF-QP Safety Filters: Analysis and Synthesis

Shima Sadat Mousavi, Pol Mestres, Aaron D. Ames

Control barrier function (CBF)-QP safety filters enforce safety by minimally modifying a nominal controller. While prior work has mainly addressed robustness of safety under uncert…

eess.SY2026

From Vertices to Convex Hulls: Certifying Set-Wise Compatibility for CBF Constraints

Shima Sadat Mousavi, Xiao Tan, Aaron D. Ames

This paper develops certificates that propagate compatibility of multiple control barrier function (CBF) constraints from sampled vertices to their convex hull. Under mild concavit…