Zobrazeno 1 - 10
of 107
pro vyhledávání: '"Francesco Biral"'
Publikováno v:
IEEE Open Journal of Intelligent Transportation Systems, Vol 5, Pp 642-655 (2024)
In the context of vehicle trajectory planning, motion primitives are trajectories connecting pairs of boundary conditions. In autonomous racing, motion primitives have been used as computationally faster alternatives to model predictive control, for
Externí odkaz:
https://doaj.org/article/076a0bab93824097a0144dcbe1924876
Publikováno v:
IEEE Access, Vol 11, Pp 124163-124180 (2023)
This paper presents a framework to plan and execute autonomous parking maneuvers in complex parking scenarios. We formulate a minimum-time optimal control problem for trajectory planning, using an indirect optimal control approach. A novel smooth pen
Externí odkaz:
https://doaj.org/article/d475bed8a47e4f98a0631f1d819a6488
Publikováno v:
IEEE Access, Vol 11, Pp 46344-46372 (2023)
This paper presents a hierarchical framework with novel analytical and neural physics-driven models, to enable the online planning and tracking of minimum-time maneuvers, for a vehicle with partially-unknown parameters. We introduce a lateral speed p
Externí odkaz:
https://doaj.org/article/a351a0266aa54ee6865c05901fe9560b
Publikováno v:
IEEE Access, Vol 9, Pp 164394-164416 (2021)
In this manuscript, we address the problem of online optimal control for torque splitting in hybrid electric vehicles that minimises fuel consumption and preserves battery life. We divide the problem into the prediction of the future velocity profile
Externí odkaz:
https://doaj.org/article/86d330b3c59f4d3cac3002f2d9e9fcea
Publikováno v:
IEEE Access, Vol 8, Pp 192041-192064 (2020)
This paper presents a novel approach to learning predictive motor control via “mental simulations”. The method, inspired by learning via mental imagery in natural Cognition, develops in two phases: first, the learning of predictive models based o
Externí odkaz:
https://doaj.org/article/ce8b882837744164a8192d9d9cef0ece
Autor:
Andrea Zignoli, Alessandro Fornasiero, Matteo Ragni, Barbara Pellegrini, Federico Schena, Francesco Biral, Paul B Laursen
Publikováno v:
PLoS ONE, Vol 15, Iss 3, p e0229466 (2020)
Measurement of oxygen uptake during exercise ([Formula: see text]) is currently non-accessible to most individuals without expensive and invasive equipment. The goal of this pilot study was to estimate cycling [Formula: see text] from easy-to-obtain
Externí odkaz:
https://doaj.org/article/deed9ed51f1549c69c7693026a629025
Autor:
Maria Gkemou, Francesco Biral, Ioannis Gkragkopoulos, Giammarco Valenti, Ioannis Tsetsinas, Evangelos Bekiaris, Andrea Steccanella
Publikováno v:
Safety, Vol 7, Iss 2, p 39 (2021)
Cooperative intelligent transport systems (C-ITS) are expected to considerably influence road safety, traffic efficiency and comfort. Nevertheless, their market penetration is still limited, on the one hand due to the high costs of installation and m
Externí odkaz:
https://doaj.org/article/56f6ce14a7c249b6a4b603c7cb488f94
Effect of control variable selection in minimum-time optimal control problems for racing motorcycles
Autor:
Mattia Piazza, Francesco Biral
The paper compare optimal control problems solution with 4 different dynamic models with increasing accuracy and complexity. Two of the four models are derived from literature while other two are novel works. Upon analysis of the results, disparities
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3d030f242b116e67af1924999ebab2d0
In this letter, the authors have assessed the robustness of an Economic Nonlinear Model-Predictive Controller (ENMPC) aimed at maximizing the power production of wind turbines. The scope of this letter is to quantify the sensitivity of this type of c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f830677f53447969fa0aff5c30077cc2
https://hdl.handle.net/11590/438606
https://hdl.handle.net/11590/438606