3 citations · 3 across the 2 of their papers we have counts for
8 papers
Data-Driven Stabilization of Continuous-Time LTI Systems from Noisy Input-Output Data
Alessandro Bosso, Marco Borghesi, Andrea Iannelli +2
We present an approach to compute stabilizing controllers for continuous-time linear time-invariant systems directly from an input-output trajectory affected by process and measure…
DATA-DRIVEN PRONTO: a Model-free Solution for Numerical Optimal Control
Marco Borghesi, Lorenzo Sforni, Giuseppe Notarstefano
This article addresses the problem of data-driven numerical optimal control for unknown nonlinear systems. In our scenario, we suppose to have the possibility of performing multipl…
Data-Driven Control of Continuous-Time LTI Systems via Non-Minimal Realizations
Alessandro Bosso, Marco Borghesi, Andrea Iannelli +2
This article proposes an approach to design output-feedback controllers for unknown continuous-time linear time-invariant systems using only input-output data from a single experim…
Distributed equilibrium seeking in aggregative games: linear convergence under singular perturbations lens
Guido Carnevale, Filippo Fabiani, Filiberto Fele +2
We present a fully-distributed algorithm for Nash equilibrium seeking in aggregative games over networks. The proposed scheme endows each agent with a gradient-based scheme equippe…
Data-Driven Distributed Optimization via Aggregative Tracking and Deep-Learning
Riccardo Brumali, Guido Carnevale, Giuseppe Notarstefano
In this paper, we propose a novel distributed data-driven optimization scheme. In detail, we focus on the so-called aggregative framework, a scenario in which a set of agents aim t…
On Sufficient Richness for Linear Time-Invariant Systems
Marco Borghesi, Simone Baroncini, Guido Carnevale +2
Persistent excitation (PE) is a necessary and sufficient condition for uniform exponential parameter convergence in several adaptive, identification, and learning schemes. In this…