Zobrazit minimální záznam

dc.contributor.authorŠantin, Ondřej
dc.contributor.authorJarošová, Marta
dc.contributor.authorHavlena, Vladimír
dc.contributor.authorDostál, Zdeněk
dc.date.accessioned2017-05-16T06:59:59Z
dc.date.available2017-05-16T06:59:59Z
dc.date.issued2017
dc.identifier.citationOptimization Methods and Software. 2017, vol. 32, issue 3, p. 436-454.cs
dc.identifier.issn1055-6788
dc.identifier.issn1029-4937
dc.identifier.urihttp://hdl.handle.net/10084/117059
dc.description.abstractWe propose an algorithm for the effective solution of quadratic programming (QP) problems arising from model predictive control (MPC). MPC is a modern multivariable control method which gives the solution for a QP problem at each sample instant. Our algorithm combines the active-set strategy with the proportioning test to decide when to leave the actual active set. For the minimization in the face, we use a direct solver implemented by the Cholesky factors updates. The performance of the algorithm is illustrated by numerical experiments, and the results are compared with the state-of-the-art solvers on benchmarks from MPC.cs
dc.language.isoencs
dc.publisherTaylor & Franciscs
dc.relation.ispartofseriesOptimization Methods and Softwarecs
dc.relation.urihttp://dx.doi.org/10.1080/10556788.2016.1213840cs
dc.subjectquadratic programmingcs
dc.subjectmodel predictive controlcs
dc.subjectactive-set strategycs
dc.titleProportioning with second-order information for model predictive controlcs
dc.typearticlecs
dc.identifier.doi10.1080/10556788.2016.1213840
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume32cs
dc.description.issue3cs
dc.description.lastpage454cs
dc.description.firstpage436cs
dc.identifier.wos000399480200002


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