Lorenzo Sforni

12 papers A* 1C 1Journal 7Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
Sparse Data-Driven LQR via Augmented Lagrangian-Based Policy Search.
IEEE Trans. Control. Netw. Syst.
Lorenzo Sforni, Ivano Notarnicola, Giuseppe Notarstefano
2025 J jnl
A Distributed Feedback-Based Framework for Nonlinear Aggregative Optimal Control.
IEEE Trans. Autom. Control.
Lorenzo Sforni, Guido Carnevale, Giuseppe Notarstefano
2025 J jnl
DATA-DRIVEN PRONTO: a Model-free Solution for Numerical Optimal Control.
CoRR
Marco Borghesi, Lorenzo Sforni, Giuseppe Notarstefano
2024 J jnl
Multi-Robot Target Monitoring and Encirclement via Triggered Distributed Feedback Optimization.
CoRR
Lorenzo Pichierri, Guido Carnevale, Lorenzo Sforni, Giuseppe Notarstefano
2024 C conf
Receding Horizon CBF-Based Multi-Layer Controllers for Safe Trajectory Generation.
ACC
Lorenzo Sforni, Giuseppe Notarstefano, Aaron D. Ames
2024 J jnl
Stability-Certified On-Policy Data-Driven LQR via Recursive Learning and Policy Gradient.
CoRR
Lorenzo Sforni, Guido Carnevale, Ivano Notarnicola, Giuseppe Notarstefano
2023 A* conf
A Distributed Online Optimization Strategy for Cooperative Robotic Surveillance.
ICRA
Lorenzo Pichierri, Guido Carnevale, Lorenzo Sforni, Andrea Testa, Giuseppe Notarstefano
2023 J jnl
A Distributed Online Optimization Strategy for Cooperative Robotic Surveillance.
CoRR
Lorenzo Pichierri, Guido Carnevale, Lorenzo Sforni, Andrea Testa, Giuseppe Notarstefano
2023 — conf
On-Policy Data-Driven Linear Quadratic Regulator via Combined Policy Iteration and Recursive Least Squares.
CDC
Lorenzo Sforni, Guido Carnevale, Ivano Notarnicola, Giuseppe Notarstefano
2022 — conf
Structured-policy Q-learning: an LMI-based Design Strategy for Distributed Reinforcement Learning.
CDC
Lorenzo Sforni, Andrea Camisa, Giuseppe Notarstefano
2021 J jnl
GoPRONTO: a Feedback-based Framework for Nonlinear Optimal Control.
CoRR
Lorenzo Sforni, Sara Spedicato, Ivano Notarnicola, Giuseppe Notarstefano
2021 — conf
Learning-driven Nonlinear Optimal Control via Gaussian Process Regression.
CDC
Lorenzo Sforni, Ivano Notarnicola, Giuseppe Notarstefano