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20212025
most citedUncertainty-aware data-driven predictive control in a stochastic setting

16 citations · 118 across the 18 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

eess.SY2023★ 15 cited

Harnessing Uncertainty for a Separation Principle in Direct Data-Driven Predictive Control

Alessandro Chiuso, Marco Fabris, Valentina Breschi +1

Model Predictive Control (MPC) is a powerful method for complex system regulation, but its reliance on an accurate model poses many limitations in real-world applications. Data-dri…

eess.SY2023★ 7 cited

Optimal Time-Invariant Distributed Formation Tracking for Second-Order Multi-Agent Systems

Marco Fabris, Giulio Fattore, Angelo Cenedese

This paper addresses the optimal time-invariant formation tracking problem with the aim of providing a distributed solution for multi-agent systems with second-order integrator dyn…

eess.SY2023★ 6 cited

Adaptive Consensus-based Reference Generation for the Regulation of Open-Channel Networks

Marco Fabris, Marco D. Bellinazzi, Andrea Furlanetto +1

This paper deals with water management over open-channel networks (OCNs) subject to water height imbalance. The OCN is modeled by means of graph theoretic tools and a regulation sc…

eess.SY2023★ 6 cited

A Robustness Analysis to Structured Channel Tampering Over Secure-by-Design Consensus Networks

Marco Fabris, Daniel Zelazo

This work addresses multi-agent consensus networks where adverse attackers affect the convergence performances of the protocol by manipulating the edge weights. We generalize (Fabr…

eess.SY2023

On the Characterization of Regular Ring Lattices and their Relation with the Dirichlet Kernel

Marco Fabris

Regular ring lattices (RRLs) are defined as peculiar undirected circulant graphs constructed from a cycle graph, wherein each node is connected to pairs of neighbors that are space…

eess.SY2023★ 11 cited

On the impact of regularization in data-driven predictive control

Valentina Breschi, Alessandro Chiuso, Marco Fabris +1

Model predictive control (MPC) is a control strategy widely used in industrial applications. However, its implementation typically requires a mathematical model of the system being…