dc.creatorSanchez, Ignacio
dc.creatorDJorge, Agustina
dc.creatorFerramosca, Antonio
dc.creatorRaffo, Guilherme
dc.creatorGonzález, Alejandro Hernán
dc.date.accessioned2021-07-20T12:39:45Z
dc.date.accessioned2022-10-15T11:41:23Z
dc.date.available2021-07-20T12:39:45Z
dc.date.available2022-10-15T11:41:23Z
dc.date.created2021-07-20T12:39:45Z
dc.date.issued2019
dc.identifierModel Predictive Path Following and Trajectory Tracking Control using Artificial Variables for Constrained Vehicles; XVIII Reunión de trabajo en Procesamiento de la Información y Control; Argentina; 2019; 1-6
dc.identifierhttp://hdl.handle.net/11336/136484
dc.identifierCONICET Digital
dc.identifierCONICET
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4382016
dc.description.abstractIn this article, the path following and trajectorytracking problems for constrained vehicles are tackled by meansof a unified Model Predictive Control strategy. State and inputconstrains are taken into account, and additional artificial variablesare included in the controller optimization problem to overcomeseveral feasibility problems. To illustrate the performanceof the approach we discuss the example of an autonomous vehiclesubject to input constraints.
dc.languageeng
dc.publisherInstitute of Electrical and Electronics Engineers
dc.relationinfo:eu-repo/semantics/altIdentifier/url/http://www.rpic.com.ar/
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceAnales de la XVIII Reunión de trabajo en Procesamiento de la Información y Control
dc.subjectNONLINEAR MODEL PREDICTIVE CONTROL
dc.subjectPATH FOLLOWING
dc.subjectTRAJECTORY TRACKING
dc.subjectARTIFICIAL VARIABLES
dc.titleModel Predictive Path Following and Trajectory Tracking Control using Artificial Variables for Constrained Vehicles
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.typeinfo:ar-repo/semantics/documento de conferencia


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