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dc.contributor.authorEl Hajjami, Lhoussain
dc.contributor.authorMellouli, El Mehdi
dc.contributor.authorŽuraulis, Vidas
dc.contributor.authorBerrada, Mohammed
dc.contributor.authorBoumhidi, Ismail
dc.date.accessioned2023-09-18T16:27:08Z
dc.date.available2023-09-18T16:27:08Z
dc.date.issued2023
dc.identifier.issn2076-3417
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/114096
dc.description.abstractIn this paper, a novel adaptive sliding mode controller (SMC) was designed based on a robust law considering disturbances and uncertainties for autonomous ground vehicle (AGV) longitudinal dynamics. The robust law was utilized in an innovative method involving the upper bounds of disturbances and uncertainties. Estimating this lumped uncertainty upper limit based on a neural network approach allowed its online knowledge. It guided the controller to withstand the disturbance and to compensate for the uncertainties. A stability analysis, according to Lyapunov, was completed to confirm the asymptotic convergence of the states to the desired state. The effectiveness and benefits of the planned approach were scrutinized by simulations and comparative studies.eng
dc.formatPDF
dc.format.extentp. 1-15
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyINSPEC
dc.relation.isreferencedbyDOAJ
dc.relation.isreferencedbyScopus
dc.rightsLaisvai prieinamas internete
dc.source.urihttps://www.mdpi.com/2076-3417/13/1/501
dc.source.urihttps://talpykla.elaba.lt/elaba-fedora/objects/elaba:150731839/datastreams/MAIN/content
dc.titleA robust intelligent controller for autonomous ground vehicle longitudinal dynamics
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.accessRightsThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/ 4.0/).
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references46
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionSidi Mohamed Ben Abdellah University
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyTransporto inžinerijos fakultetas / Faculty of Transport Engineering
dc.subject.researchfieldT 003 - Transporto inžinerija / Transport engineering
dc.subject.studydirectionE12 - Transporto inžinerija / Transport engineering
dc.subject.vgtuprioritizedfieldsTD0101 - Autonominis sausumos ir oro transportas / Autonomous land and air transport
dc.subject.ltspecializationsL106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies
dc.subject.enautonomous ground vehicles
dc.subject.enrobust adaptive SMC
dc.subject.envehicle longitudinal dynamics
dc.subject.enneural-network-based control
dcterms.sourcetitleApplied sciences: Special issue: Advances in vehicle dynamics and road safety: Technologies, simulations and applications
dc.description.issueiss. 1
dc.description.volumevol. 13
dc.publisher.nameMDPI
dc.publisher.cityBasel
dc.identifier.doi000909269000001
dc.identifier.doi10.3390/app13010501
dc.identifier.elaba150731839


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