Advanced Data Methods for Improved Tiltrotor Test and Design

Información del proyecto

ADMITTED

Identificador del acuerdo de subvención: 832003

DOI 10.3030/832003

Proyecto cerrado

Fecha de la firma de la CE 15 Febrero 2019

Fecha de inicio 1 Febrero 2019

Fecha de finalización 30 Noviembre 2023

Financiado con arreglo a

• SOCIETAL CHALLENGES - Smart, Green And Integrated Transport

Coste total € 1 718 330,00

Aportación de la UE € 1 718 330,00

Coordinado por

TXT E-TECH SRL
Italy

Resultado final

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.

Publicaciones

Conference proceedings (3)

Model Structures and Fitting Criteria for System Identification with Neural Networks

Autores: Marco Forgione, Dario Piga
Publicado en: 2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT), 2020, Página(s) 1-6, ISBN 978-1-7281-7386-3
Editor: IEEE
DOI: 10.1109/aict50176.2020.9368834

Efficient Calibration of Embedded MPC

Autores: Marco Forgione, Dario Piga, Alberto Bemporad
Publicado en: IFAC-PapersOnLine, Edición 53/2, 2020, Página(s) 5189-5194, ISSN 2405-8963
Editor: Arxiv
DOI: 10.1016/j.ifacol.2020.12.1188

Building Digital Transformation to improve NGCTR design and simulation

Autores: Michele Sesana, Alessandro Pietro Bardelli
Publicado en: IOP Conference Series: Materials Science and Engineering, Edición 1024, 2021, Página(s) 012103, ISSN 1757-899X
Editor: iopscience.iop.org
DOI: 10.1088/1757-899x/1024/1/012103

Peer reviewed articles (5)

Integrated Neural Networks for Nonlinear Continuous-Time System Identification

Autores: Bojan Mavkov, Marco Forgione, Dario Piga
Publicado en: IEEE Control Systems Letters, 2021, Página(s) 1-1, ISSN 2475-1456
Editor: IEEE Control s\Systems Letters
DOI: 10.1109/lcsys.2020.2994806

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

Autores: Marco Forgione, Dario Piga
Publicado en: European Journal of Control, Edición 59, 2021, Página(s) 69-81, ISSN 0947-3580
Editor: Lavoisier
DOI: 10.1016/j.ejcon.2021.01.008

Neural State-Space Models: Empirical Evaluation of Uncertainty Quantification

Autores: Marco Forgione; Dario Piga
Publicado en: 22nd IFAC World Congress: Yokohama, Japan, July 9-14, 2023, Edición Volume 56, Edición 2, 2023, 2023, Página(s) 4082 - 4087, ISSN 2405-8963
Editor: Elsevier
DOI: 10.1016/j.ifacol.2023.10.1736

Deep learning with transfer functions: new applications in system identification

Autores: Dario Piga, Marco Forgione, Manas Mejari
Publicado en: IFAC-PapersOnLine, Edición 54/7, 2021, Página(s) 415-420, ISSN 2405-8963
Editor: Elsevier
DOI: 10.1016/j.ifacol.2021.08.395

Learning dynamical systems from quantized observations: a Bayesian perspective

Autores: Dario Piga; Manas Mejari; Marco Forgione
Publicado en: IEEE Transactions on Automatic Control, Edición Volume 67, Edición 10, Oct. 2022, 2022, Página(s) 5471 - 5478, ISSN 0018-9286
Editor: 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

Autores: Marco Forgione, Dario Piga
Publicado en: International Journal of Adaptive Control and Signal Processing, Edición 35/4, 2021, Página(s) 612-626, ISSN 0890-6327
Editor: John Wiley & Sons Inc.
DOI: 10.1002/acs.3216