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20222026
most citedRobust stabilization of polytopic systems via fast and reliable neural network-based approximations

4 citations · 4 across the 5 of their papers we have counts for

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5 papers

math.OC2026

Learning Over-Relaxation Policies for ADMM with Convergence Guarantees

Junan Lin, Paul J. Goulart, Luca Furieri

The Alternating Direction Method of Multipliers (ADMM) is a widely used method for structured convex optimization, and its practical performance depends strongly on the choice of p…

math.OC2025

Data-Driven Performance Guarantees for Parametric Optimization Problems

Jingyi Huang, Paul Goulart, Kostas Margellos

We propose a data-driven method to establish probabilistic performance guarantees for parametric optimization problems solved via iterative algorithms. Our approach addresses two k…

math.OC2025

Synthesis of safety certificates for discrete-time uncertain systems via convex optimization

Marta Fochesato, Han Wang, Antonis Papachristodoulou +1

We study the problem of co-designing control barrier functions and linear state feedback controllers for discrete-time linear systems affected by additive disturbances. For disturb…

math.OC2025

Predictive Control Barrier Functions: Bridging model predictive control and control barrier functions

Jingyi Huang, Han Wang, Kostas Margellos +1

In this paper, we establish a connection between model predictive control (MPC) techniques and Control Barrier Functions (CBFs). Recognizing the similarity between CBFs and Control…

eess.SY2022★ 4 cited

Robust stabilization of polytopic systems via fast and reliable neural network-based approximations

Filippo Fabiani, Paul J. Goulart

We consider the design of fast and reliable neural network (NN)-based approximations of traditional stabilizing controllers for linear systems with polytopic uncertainty, including…