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20182022
most citedModel Identification and Adaptive State Observation for a Class of Nonlinear Systems

32 citations · 32 across the 3 of their papers we have counts for

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eess.SY2022

Data-driven Output Regulation via Gaussian Processes and Luenberger Internal Models

Lorenzo Gentilini, Michelangelo Bin, Lorenzo Marconi

This paper deals with the problem of adaptive output regulation for multivariable nonlinear systems by presenting a learning-based adaptive internal model-based design strategy. Th…

eess.SY2020

A Distributed Methodology for Approximate Uniform Global Minimum Sharing

Michelangelo Bin, Thomas Parisini

The paper deals with the distributed minimum sharing problem: a set of decision-makers compute the minimum of some local quantities of interest in a distributed and decentralized w…

eess.SY202032 cited

Model Identification and Adaptive State Observation for a Class of Nonlinear Systems

Michelangelo Bin, Lorenzo Marconi

In this paper we consider the joint problems of state estimation and model identification for a class of continuous-time nonlinear systems in output-feedback canonical form. An ada…

eess.SY2020

About Robustness of Control Systems Embedding an Internal Model

Michelangelo Bin, Daniele Astolfi, Lorenzo Marconi

Robustness is a basic property of any control system. In the context of linear output regulation, it was proved that embedding an internal model of the exogenous signals is necessa…

eess.SY2019

A System Theoretical Perspective to Gradient-Tracking Algorithms for Distributed Quadratic Optimization

Michelangelo Bin, Ivano Notarnicola, Lorenzo Marconi +1

In this paper we consider a recently developed distributed optimization algorithm based on gradient tracking. We propose a system theory framework to analyze its structural propert…

eess.SY2019

Approximate Nonlinear Regulation via Identification-Based Adaptive Internal Models

Michelangelo Bin, Pauline Bernard, Lorenzo Marconi

This paper concerns the problem of adaptive output regulation for multivariable nonlinear systems in normal form. We present a regulator employing an adaptive internal model of the…