Advanced Data Methods for Improved Tiltrotor Test and Design

Informations projet

ADMITTED

N° de convention de subvention: 832003

DOI 10.3030/832003

Projet clôturé

Date de signature de la CE 15 Février 2019

Date de début 1 Février 2019

Date de fin 30 Novembre 2023

Financé au titre de

• SOCIETAL CHALLENGES - Smart, Green And Integrated Transport

Coût total € 1 718 330,00

Contribution de l’UE € 1 718 330,00

Coordonné par

TXT E-TECH SRL
Italy

Livrables

Documents, reports (1)

Dissemination strategy and plan, Project website and media content

This deliverable provides the overall project dissemination strategy and plan as well as will ensure the public website at M3 for the project is up and running since the first month of the project, and will also populate it with the initial contents, including a one-pager leaflet for the early dissemination.

Publications

Conference proceedings (3)

Model Structures and Fitting Criteria for System Identification with Neural Networks

Auteurs: Marco Forgione, Dario Piga
Publié dans: 2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT), 2020, Page(s) 1-6, ISBN 978-1-7281-7386-3
Éditeur: IEEE
DOI: 10.1109/aict50176.2020.9368834

Efficient Calibration of Embedded MPC

Auteurs: Marco Forgione, Dario Piga, Alberto Bemporad
Publié dans: IFAC-PapersOnLine, Numéro 53/2, 2020, Page(s) 5189-5194, ISSN 2405-8963
Éditeur: Arxiv
DOI: 10.1016/j.ifacol.2020.12.1188

Building Digital Transformation to improve NGCTR design and simulation

Auteurs: Michele Sesana, Alessandro Pietro Bardelli
Publié dans: IOP Conference Series: Materials Science and Engineering, Numéro 1024, 2021, Page(s) 012103, ISSN 1757-899X
Éditeur: iopscience.iop.org
DOI: 10.1088/1757-899x/1024/1/012103

Peer reviewed articles (5)

Integrated Neural Networks for Nonlinear Continuous-Time System Identification

Auteurs: Bojan Mavkov, Marco Forgione, Dario Piga
Publié dans: IEEE Control Systems Letters, 2021, Page(s) 1-1, ISSN 2475-1456
Éditeur: IEEE Control s\Systems Letters
DOI: 10.1109/lcsys.2020.2994806

Continuous-time system identification with neural networks: Model structures and fitting criteria

Auteurs: Marco Forgione, Dario Piga
Publié dans: European Journal of Control, Numéro 59, 2021, Page(s) 69-81, ISSN 0947-3580
Éditeur: Lavoisier
DOI: 10.1016/j.ejcon.2021.01.008

Neural State-Space Models: Empirical Evaluation of Uncertainty Quantification

Auteurs: Marco Forgione; Dario Piga
Publié dans: 22nd IFAC World Congress: Yokohama, Japan, July 9-14, 2023, Numéro Volume 56, Numéro 2, 2023, 2023, Page(s) 4082 - 4087, ISSN 2405-8963
Éditeur: Elsevier
DOI: 10.1016/j.ifacol.2023.10.1736

Deep learning with transfer functions: new applications in system identification

Auteurs: Dario Piga, Marco Forgione, Manas Mejari
Publié dans: IFAC-PapersOnLine, Numéro 54/7, 2021, Page(s) 415-420, ISSN 2405-8963
Éditeur: Elsevier
DOI: 10.1016/j.ifacol.2021.08.395

Learning dynamical systems from quantized observations: a Bayesian perspective

Auteurs: Dario Piga; Manas Mejari; Marco Forgione
Publié dans: IEEE Transactions on Automatic Control, Numéro Volume 67, Numéro 10, Oct. 2022, 2022, Page(s) 5471 - 5478, ISSN 0018-9286
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tac.2021.3122385

Non-peer reviewed articles (1)

dynoNet : A neural network architecture for learning dynamical systems

Auteurs: Marco Forgione, Dario Piga
Publié dans: International Journal of Adaptive Control and Signal Processing, Numéro 35/4, 2021, Page(s) 612-626, ISSN 0890-6327
Éditeur: John Wiley & Sons Inc.
DOI: 10.1002/acs.3216