dc.creatorBiagiola, Silvina Ines
dc.creatorFigueroa, Jose Luis
dc.date.accessioned2018-10-10T20:02:21Z
dc.date.accessioned2018-11-06T12:36:09Z
dc.date.available2018-10-10T20:02:21Z
dc.date.available2018-11-06T12:36:09Z
dc.date.created2018-10-10T20:02:21Z
dc.date.issued2016-05
dc.identifierBiagiola, Silvina Ines; Figueroa, Jose Luis; Robust Control Approach for Volterra Models; Institute of Electrical and Electronics Engineers; IEEE Latin America Transactions; 14; 5; 5-2016; 2146-2151
dc.identifier1548-0992
dc.identifierhttp://hdl.handle.net/11336/62127
dc.identifierCONICET Digital
dc.identifierCONICET
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1868189
dc.description.abstractRecently, different algorithms for identification of several uncertain nonlinear models, referred to as Volterra-type models, were introduced in the literature. This work deals with the development of a suitable robust model predictive control (MPC) scheme able to cope with the uncertain characterization of those types of models. A discrete-time multivariable algorithm with efficient computational performance is developed. A simulation example based on a multivariable distillation column is introduced to illustrate the behavior of this methodology under the presence of uncertainties and constraints on the manipulated and controlled variables.
dc.languagespa
dc.publisherInstitute of Electrical and Electronics Engineers
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.1109/TLA.2016.7530407
dc.relationinfo:eu-repo/semantics/altIdentifier/url/https://ieeexplore.ieee.org/document/7530407
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectMODEL
dc.subjectMODEL PREDICTIVE CONTROL
dc.subjectNONLINEAR
dc.subjectROBUST CONTROL
dc.subjectVOLTERRA
dc.titleRobust Control Approach for Volterra Models
dc.typeArtículos de revistas
dc.typeArtículos de revistas
dc.typeArtículos de revistas


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