Zobrazeno 1 - 10
of 74
pro vyhledávání: '"Gian Paolo Incremona"'
Publikováno v:
IEEE Open Journal of Intelligent Transportation Systems, Vol 3, Pp 799-812 (2022)
In this paper a novel hierarchical multi-level control scheme is proposed for freeway traffic systems. Relying on a coupled PDE-ODE nominal model, capturing the interaction between the macroscopic traffic flow and a platoon of connected and automated
Externí odkaz:
https://doaj.org/article/8111249bd2db4cdba2d48ca0fc7c14bd
Publikováno v:
Energies, Vol 14, Iss 15, p 4389 (2021)
Recently, the introduction of electric vehicles has given rise to a new paradigm in the transportation field, spurring the public transport service in the direction of using completely electric bus fleets. In this context, one of the main challenges
Externí odkaz:
https://doaj.org/article/14d96d4aff7c4553b0c6a2393e795f49
Shared Control of Robot Manipulators With Obstacle Avoidance: A Deep Reinforcement Learning Approach
Autor:
Matteo Rubagotti, Bianca Sangiovanni, Aigerim Nurbayeva, Gian Paolo Incremona, Antonella Ferrara, Almas Shintemirov
Publikováno v:
IEEE Control Systems. 43:44-63
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cfe72468ff79410e026a1e1d96915b63
https://doi.org/10.1109/mcs.2022.3216653
https://doi.org/10.1109/mcs.2022.3216653
Publikováno v:
IEEE Transactions on Intelligent Vehicles. 8:469-480
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c13d035a77b30ac0f23d52032736a7b2
https://doi.org/10.1109/tiv.2022.3140484
https://doi.org/10.1109/tiv.2022.3140484
Publikováno v:
IEEE Transactions on Automatic Control. :1-8
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::86e373f2e7322e5004e5f442ad60d9bd
https://doi.org/10.1109/tac.2023.3275496
https://doi.org/10.1109/tac.2023.3275496
Publikováno v:
IEEE Control Systems Letters. 6:2623-2628
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::75e78bfe59a8ada715fcc061f9ac1f55
https://doi.org/10.1109/lcsys.2022.3172729
https://doi.org/10.1109/lcsys.2022.3172729
Publikováno v:
IEEE Control Systems Letters. 6:446-451
This note proposes a novel architecture of integral sliding mode control, in which a special “ideal control” part is introduced. This part incorporates a fairly general form of internal model to deal with regular (i.e., modeled) persistent distur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b46ccd221f2703fca62fc57c644b362b
https://doi.org/10.1109/lcsys.2021.3079187
https://doi.org/10.1109/lcsys.2021.3079187
Publikováno v:
International Journal of Robust and Nonlinear Control.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5411cf095c7cbcdc63eaa3e9e71f0fe
https://doi.org/10.1002/rnc.6608
https://doi.org/10.1002/rnc.6608
Publikováno v:
IEEE transactions on automatic control
(2021). doi:10.1109/TAC.2021.3056398
info:cnr-pdr/source/autori:Possieri, Corrado; Incremona, Gian Paolo; Calafiore, Giuseppe C.; Ferrara, Antonella/titolo:An Iterative Data-Driven Linear Quadratic Method to Solve Nonlinear Discrete-Time Tracking Problems/doi:10.1109%2FTAC.2021.3056398/rivista:IEEE transactions on automatic control (Print)/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume
(2021). doi:10.1109/TAC.2021.3056398
info:cnr-pdr/source/autori:Possieri, Corrado; Incremona, Gian Paolo; Calafiore, Giuseppe C.; Ferrara, Antonella/titolo:An Iterative Data-Driven Linear Quadratic Method to Solve Nonlinear Discrete-Time Tracking Problems/doi:10.1109%2FTAC.2021.3056398/rivista:IEEE transactions on automatic control (Print)/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume
The objective of this note is to introduce a novel data-driven iterative linear quadratic control method for solving a class of nonlinear optimal tracking problems. Specifically, an algorithm is proposed to approximate the Q-factors arising from line
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c982ebd7aed97fbfe6d78c5a61b4a90e
https://doi.org/10.1109/tac.2021.3056398
https://doi.org/10.1109/tac.2021.3056398