93 citations · 375 across the 30 of their papers we have counts for
8 papers · 1 filter
Q-SHED: Distributed Optimization at the Edge via Hessian Eigenvectors Quantization
Nicolò Dal Fabbro, Michele Rossi, Luca Schenato +1
Edge networks call for communication efficient (low overhead) and robust distributed optimization (DO) algorithms. These are, in fact, desirable qualities for DO frameworks, such a…
Can Competition Outperform Collaboration? The Role of Misbehaving Agents
Luca Ballotta, Giacomo Como, Jeff S. Shamma +1
We investigate a novel approach to resilient distributed optimization with quadratic costs in a multi-agent system prone to unexpected events that make some agents misbehave. In co…
Self-triggered MPC robust to bounded packet loss via a min-max approach: extended version
Stefan Wildhagen, Matthias Pezzutto, Luca Schenato +1
Networked Control Systems typically come with a limited communication bandwidth and thus require special care when designing the underlying control and triggering law. A method tha…
Competition-Based Resilience in Distributed Quadratic Optimization
Luca Ballotta, Giacomo Como, Jeff S. Shamma +1
This paper proposes a novel approach to resilient distributed optimization with quadratic costs in a networked control system (e.g., wireless sensor network, power grid, robotic te…
Transmission Power Allocation for Remote Estimation with Multi-packet Reception Capabilities
Matthias Pezzutto, Luca Schenato, Subhrakanti Dey
In this paper we consider the problem of transmission power allocation for remote estimation of a dynamical system in the case where the estimator is able to simultaneously receive…
Optimal Network Topology of Multi-Agent Systems subject to Computation and Communication Latency (with proofs)
Luca Ballotta, Mihailo R. Jovanović, Luca Schenato
We study minimum-variance feedback-control design for a networked control system with retarded dynamics, where inter-agent communication is subject to latency. We prove that such a…
Accelerated Probabilistic State Estimation in Distribution Grids via Model Order Reduction
Samuel Chevalier, Luca Schenato, Luca Daniel
This paper applies a custom model order reduction technique to the distribution grid state estimation problem. Specifically, the method targets the situation where, due to pseudo-m…
Accelerated Probabilistic Power Flow in Electrical Distribution Networks via Model Order Reduction and Neumann Series Expansion
Samuel Chevalier, Luca Schenato, Luca Daniel
This paper develops a computationally efficient algorithm which speeds up the probabilistic power flow (PPF) problem by exploiting the inherently low-rank nature of the voltage pro…