Advanced Data Methods for Improved Tiltrotor Test and Design

Informacje na temat projektu

ADMITTED

Identyfikator umowy o grant: 832003

DOI 10.3030/832003

Projekt został zamknięty

Data podpisania przez KE 15 Lutego 2019

Data rozpoczęcia 1 Lutego 2019

Data zakończenia 30 Listopada 2023

Finansowanie w ramach

• SOCIETAL CHALLENGES - Smart, Green And Integrated Transport

Koszt całkowity € 1 718 330,00

Wkład UE € 1 718 330,00

Koordynowany przez

TXT E-TECH SRL
Italy

Rezultaty

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.

Publikacje

Conference proceedings (3)

Model Structures and Fitting Criteria for System Identification with Neural Networks

Autorzy: Marco Forgione, Dario Piga
Opublikowane w: 2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT), 2020, Strona(/y) 1-6, ISBN 978-1-7281-7386-3
Wydawca: IEEE
DOI: 10.1109/aict50176.2020.9368834

Efficient Calibration of Embedded MPC

Autorzy: Marco Forgione, Dario Piga, Alberto Bemporad
Opublikowane w: IFAC-PapersOnLine, Numer 53/2, 2020, Strona(/y) 5189-5194, ISSN 2405-8963
Wydawca: Arxiv
DOI: 10.1016/j.ifacol.2020.12.1188

Building Digital Transformation to improve NGCTR design and simulation

Autorzy: Michele Sesana, Alessandro Pietro Bardelli
Opublikowane w: IOP Conference Series: Materials Science and Engineering, Numer 1024, 2021, Strona(/y) 012103, ISSN 1757-899X
Wydawca: iopscience.iop.org
DOI: 10.1088/1757-899x/1024/1/012103

Peer reviewed articles (5)

Integrated Neural Networks for Nonlinear Continuous-Time System Identification

Autorzy: Bojan Mavkov, Marco Forgione, Dario Piga
Opublikowane w: IEEE Control Systems Letters, 2021, Strona(/y) 1-1, ISSN 2475-1456
Wydawca: IEEE Control s\Systems Letters
DOI: 10.1109/lcsys.2020.2994806

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

Autorzy: Marco Forgione, Dario Piga
Opublikowane w: European Journal of Control, Numer 59, 2021, Strona(/y) 69-81, ISSN 0947-3580
Wydawca: Lavoisier
DOI: 10.1016/j.ejcon.2021.01.008

Neural State-Space Models: Empirical Evaluation of Uncertainty Quantification

Autorzy: Marco Forgione; Dario Piga
Opublikowane w: 22nd IFAC World Congress: Yokohama, Japan, July 9-14, 2023, Numer Volume 56, Numer 2, 2023, 2023, Strona(/y) 4082 - 4087, ISSN 2405-8963
Wydawca: Elsevier
DOI: 10.1016/j.ifacol.2023.10.1736

Deep learning with transfer functions: new applications in system identification

Autorzy: Dario Piga, Marco Forgione, Manas Mejari
Opublikowane w: IFAC-PapersOnLine, Numer 54/7, 2021, Strona(/y) 415-420, ISSN 2405-8963
Wydawca: Elsevier
DOI: 10.1016/j.ifacol.2021.08.395

Learning dynamical systems from quantized observations: a Bayesian perspective

Autorzy: Dario Piga; Manas Mejari; Marco Forgione
Opublikowane w: IEEE Transactions on Automatic Control, Numer Volume 67, Numer 10, Oct. 2022, 2022, Strona(/y) 5471 - 5478, ISSN 0018-9286
Wydawca: 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

Autorzy: Marco Forgione, Dario Piga
Opublikowane w: International Journal of Adaptive Control and Signal Processing, Numer 35/4, 2021, Strona(/y) 612-626, ISSN 0890-6327
Wydawca: John Wiley & Sons Inc.
DOI: 10.1002/acs.3216