dc.creatorSouto R.F.
dc.creatorDo Val J.B.R.
dc.creatorOliveira R.C.L.F.
dc.date2013
dc.date2015-06-25T19:16:02Z
dc.date2015-11-26T15:13:56Z
dc.date2015-06-25T19:16:02Z
dc.date2015-11-26T15:13:56Z
dc.date.accessioned2018-03-28T22:24:04Z
dc.date.available2018-03-28T22:24:04Z
dc.identifier9781467357173
dc.identifierProceedings Of The Ieee Conference On Decision And Control. Institute Of Electrical And Electronics Engineers Inc., v. , n. , p. 1886 - 1891, 2013.
dc.identifier1912216
dc.identifier10.1109/CDC.2013.6760157
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84902340647&partnerID=40&md5=3941790a8098bed316fb2480f2689781
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/89390
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/89390
dc.identifier2-s2.0-84902340647
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1258762
dc.descriptionWe look at the situation of controlling a poorly known system, for which only a simplified and uncertain model can be used for control design purposes. This setting is commonly found in biological systems or economic policy-making. We employ the idea of the CVIU approach [1], and develop in the scalar case the solution of the HJB equation. The control design is compared with the standard and robust LQG solutions, exploring the fact that the model can be quite distinct of the actual system.We verify that in some mismatched situations the CVIU approach yields better performance than the LQG strategies. © 2013 IEEE.
dc.description
dc.description
dc.description1886
dc.description1891
dc.descriptionet al.,Honeywell,MathWorks,Springer,Taylor and Francis Group,University of Trieste
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dc.languageen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relationProceedings of the IEEE Conference on Decision and Control
dc.rightsfechado
dc.sourceScopus
dc.titleControlling Uncertain Stochastic Systems: Performance Comparisons In A Scalar System
dc.typeActas de congresos


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