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Modeling and model predictive control of a nonlinear hydraulic system

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dc.title Modeling and model predictive control of a nonlinear hydraulic system en
dc.contributor.author Chalupa, Petr
dc.contributor.author Novák, Jakub
dc.relation.ispartof Computers and Mathematics with Applications
dc.identifier.issn 0898-1221 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2013
utb.relation.volume 66
utb.relation.issue 2
dc.citation.spage 155
dc.citation.epage 164
dc.type article
dc.language.iso en
dc.publisher Pergamon Elsevier Science Ltd. en
dc.identifier.doi 10.1016/j.camwa.2013.01.021
dc.relation.uri https://www.sciencedirect.com/science/article/pii/S0898122113000382
dc.subject Global optimization en
dc.subject Model predictive control en
dc.subject Modeling en
dc.subject Nonlinear system en
dc.subject Three-tank system en
dc.description.abstract This paper deals with modeling and control of a hydraulic three-tank system. A process of creating a computer model in the MATLAB/Simulink environment is described, and optimal PID (proportional-integral-derivative) and model predictive controllers are proposed. The modeling starts with the creation of an initial mathematical model based on a first-principles approach. Then, the initial model is enhanced to obtain better correspondence with a real-time system, and parameters of the modified system are identified from measurements. The real-time system contains nonlinearities which cannot be neglected, and therefore are identified and included in the final mathematical model. The resulting model is used for a control design. As the real-time system has long time constants, usage of the Simulink model dramatically speeds up the design process. Optimal PID and model predictive controllers (MPC) are proposed and compared. Model predictive controllers for both a linearized model and the nonlinear system are proposed. The techniques described are not limited to one particular modeling problem, but can be used as an illustrative example for the modeling of many technological processes. © 2013 Elsevier Ltd. All rights reserved. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1003403
utb.identifier.obdid 43870245
utb.identifier.scopus 2-s2.0-84880203313
utb.identifier.wok 000321941300007
utb.identifier.coden CMAPD
utb.source j-scopus
dc.date.accessioned 2013-07-27T14:55:51Z
dc.date.available 2013-07-27T14:55:51Z
utb.contributor.internalauthor Chalupa, Petr
utb.contributor.internalauthor Novák, Jakub
utb.fulltext.affiliation Petr Chalupa ∗ , Jakub Novák Faculty of Applied Informatics, Tomas Bata University in Zlin, nám. T. G. Masaryka 5555, 760 01 Zlín, Czech Republic ∗ Corresponding author. Tel.: +420 57603 5204. E-mail address: chalupa@fai.utb.cz (P. Chalupa).
utb.fulltext.dates -
utb.fulltext.sponsorship This work was supported by the European Regional Development Fund under the project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089.
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.ou -
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