Marcello Farina

About Marcello Farina

Marcello Farina, With an exceptional h-index of 34 and a recent h-index of 25 (since 2020), a distinguished researcher at Politecnico di Milano, specializes in the field of Systems and Control.

His recent articles reflect a diverse array of research interests and contributions to the field:

Moving horizon partition-based state estimation of large-scale systems--Revised version

Nonlinear MPC design for incrementally ISS systems with application to GRU networks

Robust offset‐free nonlinear model predictive control for systems learned by neural nonlinear autoregressive exogenous models

Virtual reference feedback tuning for linear discrete-time systems with robust stability guarantees based on set membership

An incremental input-to-state stability condition for a class of recurrent neural networks

A novel distributed algorithm for estimation and control of large-scale systems

Deep long-short term memory networks: Stability properties and experimental validation

Data-based control design for output-error linear discrete-time systems with probabilistic stability guarantees

Marcello Farina Information

University

Position

Assistant Professor

Citations(all)

4261

Citations(since 2020)

2479

Cited By

2789

hIndex(all)

34

hIndex(since 2020)

25

i10Index(all)

84

i10Index(since 2020)

62

Email

University Profile Page

Google Scholar

Marcello Farina Skills & Research Interests

Systems and Control

Top articles of Marcello Farina

Moving horizon partition-based state estimation of large-scale systems--Revised version

arXiv preprint arXiv:2401.17933

2024/1/31

Marcello Farina
Marcello Farina

H-Index: 22

Riccardo Scattolini
Riccardo Scattolini

H-Index: 31

Nonlinear MPC design for incrementally ISS systems with application to GRU networks

Automatica

2024/1/1

Robust offset‐free nonlinear model predictive control for systems learned by neural nonlinear autoregressive exogenous models

International Journal of Robust and Nonlinear Control

2023/11/10

Virtual reference feedback tuning for linear discrete-time systems with robust stability guarantees based on set membership

Automatica

2023/11/1

Marcello Farina
Marcello Farina

H-Index: 22

An incremental input-to-state stability condition for a class of recurrent neural networks

IEEE Transactions on Automatic Control

2023/10/27

Marcello Farina
Marcello Farina

H-Index: 22

A novel distributed algorithm for estimation and control of large-scale systems

European Journal of Control

2023/7/1

Marcello Farina
Marcello Farina

H-Index: 22

Marco Rocca
Marco Rocca

H-Index: 4

Deep long-short term memory networks: Stability properties and experimental validation

2023/6/13

Data-based control design for output-error linear discrete-time systems with probabilistic stability guarantees

IEEE Control Systems Letters

2023/6/8

Andrea Bisoffi
Andrea Bisoffi

H-Index: 7

Marcello Farina
Marcello Farina

H-Index: 22

Data-based control design for nonlinear systems with recurrent neural network-based controllers

IFAC-PapersOnLine

2023/1/1

Fabio Dercole
Fabio Dercole

H-Index: 16

Marcello Farina
Marcello Farina

H-Index: 22

Design, realization, control, and validation of a smart tether system for a robotic guide for blind and visually impaired users

IFAC-PapersOnLine

2023/1/1

Marcello Farina
Marcello Farina

H-Index: 22

Manuela Galli
Manuela Galli

H-Index: 33

Dar forma a spazi pubblici accessibili per le persone con limitazioni visive. L'esperienza di ricerca BUDD-e.

TECHNE: Journal of Technology for Architecture & Environment

2023/1/1

Shaping accessible public spaces for visually impaired people. The BUDD-e research experience.

TECHNE

2023

Data-based control design for linear discrete-time systems with robust stability guarantees

2022/12/6

Marcello Farina
Marcello Farina

H-Index: 22

An Offset-Free Nonlinear MPC scheme for systems learned by Neural NARX models

2022/12/6

A feedback linearisation algorithm for single-track models with structural stability properties

Control Engineering Practice

2022/11/1

Recurrent neural network controllers learned using virtual reference feedback tuning with application to an electronic throttle body

2022/7/12

Marcello Farina
Marcello Farina

H-Index: 22

Towards lifelong learning of recurrent neural networks for control design

2022/7/12

On recurrent neural networks for learning-based control: recent results and ideas for future developments

Journal of Process Control

2022/6/1

Robust multi-rate predictive control using multi-step prediction models learned from data

Automatica

2022/2/1

METODO E SISTEMA DI GUIDA COMPRENDENTE UN CAVO DI TRAZIONE PER UTENTI CON DISABILITÀ VISIVE E ASSIEME ROBOTICO COMPRENDENTE DETTO SISTEMA

2022

See List of Professors in Marcello Farina University(Politecnico di Milano)