Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Shakiba Yaghoubi"'
Autor:
Gidon Ernst, Paolo Arcaini, Ismail Bennani, Aniruddh Chandratre, Alexandre Donzé, Georgios Fainekos, Goran Frehse, Khouloud Gaaloul, Jun Inoue, Tanmay Khandait, Logan Mathesen, Claudio Menghi, Giulia Pedrielli, Marc Pouzet, Masaki Waga, Shakiba Yaghoubi, Yoriyuki Yamagata, Zhenya Zhang
Publikováno v:
EPiC Series in Computing.
This report presents the results from the 2021 friendly competition in the ARCH work- shop for the falsification of temporal logic specifications over Cyber-Physical Systems. We briefly describe the competition settings, which have been inherited fro
Autor:
Shakiba Yaghoubi, Georgios Fainekos
Publikováno v:
ITA
In this paper, a reinforcement learning approach for designing feedback neural network controllers for nonlinear systems is proposed. Given a Signal Temporal Logic (STL) specification which needs to be satisfied by the system over a set of initial co
Autor:
Georgios Fainekos, Shakiba Yaghoubi, Tomoya Yamaguchi, Bardh Hoxha, Keyvan Majd, Danil V. Prokhorov
Publikováno v:
ACC
In this letter, we design real-time controllers that react to uncertainties with stochastic characteristics and bound the probability of a failure in finite-time to a given desired value. Stochastic control barrier functions are used to derive suffic
Publikováno v:
ITSC
Control Barrier Functions (CBF) have been recently utilized in the design of provably safe feedback control laws for nonlinear systems. These feedback control methods typically compute the next control input by solving an online Quadratic Program (QP
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62d3ed938ecad92f2257ceece06b7379
http://arxiv.org/abs/2001.08088
http://arxiv.org/abs/2001.08088
Autor:
Giulia Pedrielli, Zhenya Zhang, Gidon Ernst, Marc Pouzet, Alexandre Donzé, Claudio Menghi, Ismail Bennani, Paolo Arcaini, Goran Frehse, Yoriyuki Yamagata, Logan Mathesen, Georgios Fainekos, Shakiba Yaghoubi
Publikováno v:
ARCH
EPiC Series in Computing volume 74
info:eu-repo/grantAgreement/EC/H2020/694277
EPiC Series in Computing volume 74
info:eu-repo/grantAgreement/EC/H2020/694277
This report presents the results from the 2020 friendly competition in the ARCH workshop for the falsification of temporal logic specifications over Cyber-Physical Systems. We briefly describe the competition settings, which have been inherited from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::807596598aea11c410df7b9867d3b858
https://hdl.handle.net/10446/237254
https://hdl.handle.net/10446/237254
Publikováno v:
Iranian Journal of Science and Technology, Transactions of Mechanical Engineering. 43:415-423
Traditional methods for extremum seeking control (ESC) disregard possible prior knowledge of the system model. In practice, however, these models are usually known, but they contain uncertain parameters. Assuming that partial knowledge about the syst
Autor:
Georgios Fainekos, Adel Dokhanchi, Mohammad Hekmatnejad, Shakiba Yaghoubi, Heni Ben Amor, Aviral Shrivastava, Lina J. Karam
Publikováno v:
MEMOCODE
As Automated Vehicles (AV) get ready to hit the public roads unsupervised, many practical questions still remain open. For example, there is no commonly acceptable formal definition of what safe driving is. A formal definition of safe driving can be
Publikováno v:
CASE
This work is in the field of requirements driven search-based test case generation methods for Cyber-Physical Systems (CPS). The basic characteristic of search-based testing methods is that the search process is guided by high level requirements capt
Autor:
Shakiba Yaghoubi, Zhenya Zhang, Georgios Fainekos, Alexandre Donzé, Paolo Arcaini, Yoriyuki Yamagata, Giulia Pedrielli, Gidon Ernst, Logan Mathesen
Publikováno v:
ARCH@CPSIoTWeek
This report presents the results from the 2019 friendly competition in the ARCH workshop for the falsification of temporal logic specifications over Cyber-Physical Systems. We describe the organization of the competition and how it differs from previ
Autor:
Georgios Fainekos, Shakiba Yaghoubi
Publikováno v:
HSCC
Neural Networks (NN) have been proposed in the past as an effective means for both modeling and control of systems with very complex dynamics. However, despite the extensive research, NN-based controllers have not been adopted by the industry for saf