Constrained generalized predictive control using relaxation with quadratic penalization

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dc.contributor.authorMuñoz Infante, Carlos Alberto
dc.contributor.authorCipriano, Aldo
dc.date.accessioned2022-05-17T15:57:17Z
dc.date.available2022-05-17T15:57:17Z
dc.date.issued2001
dc.description.abstractIn this paper an iterative algorithm will be derived to find a numerical solution for the generalized predictive control of linear systems with constraints on controlled and manipulated variables. The algorithm uses the relaxation method with quadratic penalization. Conditions are proposed for the convergence of the iterative solution and results of the application to a second order linear system are presented.
dc.fuente.origenIEEE
dc.identifier.doi10.23919/ECC.2001.7076467
dc.identifier.isbn978-3952417362
dc.identifier.urihttps://doi.org/10.23919/ECC.2001.7076467
dc.identifier.urihttps://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7076467
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/64054
dc.information.autorucFacultad de matemáticas ; Muñoz Infante, Carlos Alberto ; S/I ; 84134
dc.information.autorucEscuela de ingeniería ; Cipriano Zamorano, Aldo ; S/I ; 99102
dc.language.isoen
dc.nota.accesoContenido parcial
dc.publisherIEEE
dc.relation.ispartofEuropean Control Conference (2001 : Porto, Portugal)
dc.rightsacceso restringido
dc.subjectPredictive control
dc.subjectPrediction algorithms
dc.subjectAlgorithm design and analysis
dc.subjectVectors
dc.subjectLinear programming
dc.subjectEurope
dc.subjectConvergence
dc.titleConstrained generalized predictive control using relaxation with quadratic penalizationes_ES
dc.typecomunicación de congreso
sipa.codpersvinculados84134
sipa.codpersvinculados99102
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