Advanced Data Methods for Improved Tiltrotor Test and Design

Project Information

ADMITTED

Grant agreement ID: 832003

DOI 10.3030/832003

Project closed

EC signature date 15 February 2019

Start date 1 February 2019

End date 30 November 2023

Funded under

• SOCIETAL CHALLENGES - Smart, Green And Integrated Transport

Total cost € 1 718 330,00

EU contribution € 1 718 330,00

Coordinated by

TXT E-TECH SRL
Italy

Deliverables

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

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

Efficient Calibration of Embedded MPC

Author(s): Marco Forgione, Dario Piga, Alberto Bemporad
Published in: IFAC-PapersOnLine, Issue 53/2, 2020, Page(s) 5189-5194, ISSN 2405-8963
Publisher: Arxiv
DOI: 10.1016/j.ifacol.2020.12.1188

Building Digital Transformation to improve NGCTR design and simulation

Author(s): Michele Sesana, Alessandro Pietro Bardelli
Published in: IOP Conference Series: Materials Science and Engineering, Issue 1024, 2021, Page(s) 012103, ISSN 1757-899X
Publisher: iopscience.iop.org
DOI: 10.1088/1757-899x/1024/1/012103

Peer reviewed articles (5)

Integrated Neural Networks for Nonlinear Continuous-Time System Identification

Author(s): Bojan Mavkov, Marco Forgione, Dario Piga
Published in: IEEE Control Systems Letters, 2021, Page(s) 1-1, ISSN 2475-1456
Publisher: IEEE Control s\Systems Letters
DOI: 10.1109/lcsys.2020.2994806

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

Author(s): Marco Forgione, Dario Piga
Published in: European Journal of Control, Issue 59, 2021, Page(s) 69-81, ISSN 0947-3580
Publisher: Lavoisier
DOI: 10.1016/j.ejcon.2021.01.008

Neural State-Space Models: Empirical Evaluation of Uncertainty Quantification

Author(s): Marco Forgione; Dario Piga
Published in: 22nd IFAC World Congress: Yokohama, Japan, July 9-14, 2023, Issue Volume 56, Issue 2, 2023, 2023, Page(s) 4082 - 4087, ISSN 2405-8963
Publisher: Elsevier
DOI: 10.1016/j.ifacol.2023.10.1736

Deep learning with transfer functions: new applications in system identification

Author(s): Dario Piga, Marco Forgione, Manas Mejari
Published in: IFAC-PapersOnLine, Issue 54/7, 2021, Page(s) 415-420, ISSN 2405-8963
Publisher: Elsevier
DOI: 10.1016/j.ifacol.2021.08.395

Learning dynamical systems from quantized observations: a Bayesian perspective

Author(s): Dario Piga; Manas Mejari; Marco Forgione
Published in: IEEE Transactions on Automatic Control, Issue Volume 67, Issue 10, Oct. 2022, 2022, Page(s) 5471 - 5478, ISSN 0018-9286
Publisher: 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

Author(s): Marco Forgione, Dario Piga
Published in: International Journal of Adaptive Control and Signal Processing, Issue 35/4, 2021, Page(s) 612-626, ISSN 0890-6327
Publisher: John Wiley & Sons Inc.
DOI: 10.1002/acs.3216