101 citations · 466 across the 65 of their papers we have counts for
45 papers · 1 filter
Derivative-Free Data-Driven Control of Continuous-Time Linear Time-Invariant Systems
Alessandro Bosso, Marco Borghesi, Andrea Iannelli +2
This paper develops a data-driven stabilization method for continuous-time linear time-invariant systems with theoretical guarantees and no need for signal derivatives. The framewo…
ADMM-Tracking Gradient for Distributed Optimization over Asynchronous and Unreliable Networks
Guido Carnevale, Nicola Bastianello, Giuseppe Notarstefano +1
In this paper, we propose a novel distributed algorithm for consensus optimization over networks and a robust extension tailored to deal with asynchronous agents and packet losses.…
Nonconvex Distributed Feedback Optimization for Aggregative Cooperative Robotics
Guido Carnevale, Nicola Mimmo, Giuseppe Notarstefano
Distributed aggregative optimization is a recently emerged framework in which the agents of a network want to minimize the sum of local objective functions, each one depending on t…
Uniform non-convex optimisation via Extremum Seeking
Nicola Mimmo, Lorenzo Marconi, Giuseppe Notarstefano
The paper deals with a well-known extremum seeking scheme by proving uniformity properties with respect to the amplitudes of the dither signal and of the cost function. Those prope…
Uniform quasi-convex optimisation via Extremum Seeking
Nicola Mimmo, Lorenzo Marconi, Giuseppe Notarstefano
The paper deals with a well-known extremum seeking scheme by proving uniformity properties with respect to the amplitudes of the dither signal and of the cost function. Those prope…
Triggered Gradient Tracking for Asynchronous Distributed Optimization
Guido Carnevale, Ivano Notarnicola, Lorenzo Marconi +1
This paper proposes Asynchronous Triggered Gradient Tracking, i.e., a distributed optimization algorithm to solve consensus optimization over networks with asynchronous communicati…