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Efficient deployment of remote laboratories with TwinCAT-PLCs and EjsS Plugins

dc.contributor.authorChacón Sombría, Jesús
dc.contributor.authorBesada Portas, Eva
dc.contributor.authorGarcía Pérez, Lía
dc.contributor.authorLópez Orozco, José Antonio
dc.date.accessioned2023-06-22T12:28:44Z
dc.date.available2023-06-22T12:28:44Z
dc.date.issued2022-10-06
dc.description©2022 The Authors. IFAC Symposium on Advances in Control Education (13. 2022. Hamburgo) This work has been funded by the Educational Innovation program of the Complutense University de Madrid under the 2021-39 project of the Universit
dc.description.abstractThis paper describes a new approach to streamline the development of Remote Laboratories (RL) for Control Education based on TwinCAT Programmable Logic Controllers (PLCs) and Easy JavaScript Simulations (EJsS). On one hand, the TwinCAT PLC is used to implement the laboratory back-end (responsible of closing the feedback loop over the plant under study) with industrial real-time automation methodologies. On the other hand, EJsS is used: 1) to define the RL Human-Machine Interface (HMI) front-end (used by the students to parametrize & observe the evolution of the PLC behavior and signals) and 2) to smooth and centralize the majority of the tasks that the instructors have to perform to configure and deploy the RL. This second utility of EJsS, a novelty of the RL presented in this paper, is supported by an EJsS Plugin that has been especially designed with that purpose. Besides, it is worth noting that our new RL is supported by an improved version of ReNoLabs, developed in 2016 to be a lightweight middle-ware of RLs with EJsS HMI webpages and different types of backends, whose Node.js-based server has been updated to backup the functionality of the EJsS Plugin. This paper also shows how to use our approach to setup a RL and describes the main characteristics of two RLs that have been updated with it.
dc.description.departmentSección Deptal. de Arquitectura de Computadores y Automática (Físicas)
dc.description.facultyFac. de Ciencias Físicas
dc.description.refereedTRUE
dc.description.sponsorshipUniversidad Complutense de Madrid
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/75450
dc.identifier.doi10.1016/j.ifacol.2022.09.300
dc.identifier.issn2405-8963
dc.identifier.officialurlhttp://dx.doi.org/10.1016/j.ifacol.2022.09.300
dc.identifier.urihttps://hdl.handle.net/20.500.14352/72626
dc.issue.number17
dc.journal.titleIFAC papersOnline
dc.language.isoeng
dc.page.final331
dc.page.initial326
dc.publisherElsevier
dc.relation.projectIDEducational Innovation program-2021-39 project
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.cdu004.8
dc.subject.keywordEducation
dc.subject.keywordOnline
dc.subject.keywordLabs
dc.subject.keywordVirtual and remote labs
dc.subject.keywordInternet-based control education
dc.subject.keywordEJsS
dc.subject.keywordTwinCAT PLCs
dc.subject.ucmInteligencia artificial (Informática)
dc.subject.unesco1203.04 Inteligencia Artificial
dc.titleEfficient deployment of remote laboratories with TwinCAT-PLCs and EjsS Plugins
dc.typejournal article
dc.volume.number55
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscoverye987dc75-a909-418c-93a6-23ad9eb40ce6

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