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Adaptive predictive control of three-tank-system

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dc.title Adaptive predictive control of three-tank-system en
dc.contributor.author Kubalčík, Marek
dc.contributor.author Bobál, Vladimír
dc.relation.ispartof International Journal of Mathematical Models and Methods in Applied Sciences
dc.identifier.issn 1998-0140 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2013
utb.relation.volume 7
utb.relation.issue 2
dc.citation.spage 157
dc.citation.epage 165
dc.type article
dc.language.iso en
dc.publisher North Atlantic University Union (NAUN) en
dc.relation.uri http://www.naun.org/multimedia/NAUN/ijmmas/16-692.pdf
dc.subject About four key words or phrases in alphabetical order en
dc.subject Separated by commas en
dc.description.abstract This paper is focused in application of a self - tuning predictive controller for real - time control of a three - tank - system laboratory model. The objective laboratory model is a two input - two output (TITO) nonlinear system. It is based on experience with authentic industrial control applications. The controller integrates a predictive control synthesis based on a multivariable state - space model of the controlled system and an on - line identification of an ARX model corresponding to the state - space model. The model parameters are recursively estimated using the recursive least squares method with the directional forgetting. The control algorithm is based on the Generalised Predictive Control (GPC) method. The optimization was realized by minimization of a quadratic objective function. Results of real-time experiments are also included. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1003088
utb.identifier.obdid 43869897
utb.identifier.scopus 2-s2.0-84872132482
utb.source j-scopus
dc.date.accessioned 2013-02-02T01:12:48Z
dc.date.available 2013-02-02T01:12:48Z
utb.contributor.internalauthor Kubalčík, Marek
utb.contributor.internalauthor Bobál, Vladimír
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