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Modeling and model predictive control of nonlinear hydraulic system

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dc.title Modeling and model predictive control of nonlinear hydraulic system en
dc.contributor.author Chalupa, Petr
dc.contributor.author Novák, Jakub
dc.relation.ispartof Nostradamus: Modern Methods of Prediction, Modeling and Analysis of Nonlinear Systems
dc.identifier.issn 2194-5357 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.issn 2194-5365 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-3-642-33226-5
dc.identifier.isbn 978-3-642-33227-2
dc.date.issued 2013
utb.relation.volume 192
dc.citation.spage 93
dc.citation.epage 102
dc.event.title Nostradamus Conference
dc.event.location Ostrava
utb.event.state-en Czech Republic
utb.event.state-cs Česká republika
dc.event.sdate 2012-09
dc.event.edate 2012-09
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer-Verlag Berlin en
dc.identifier.doi 10.1007/978-3-642-33227-2_12
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-642-33227-2_12
dc.description.abstract This paper deals with modeling and control of a hydraulic three tank system. A process of creating a computer model in MATLAB / Simulink environment is described and optimal PID and model predictive controllers are proposed. Modeling starts with creation of an initial mathematical model based on first principles approach. Further, the initial model is modified to obtain better correspondence with 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. Resulting model is used for control design. As the real-time system has long time constants, usage of Simulink model dramatically speeds up design process. Optimal PID and MPC controllers are proposed and compared. Described techniques are not limited to one particular modeling problem but can be used as an illustrative example for modeling of many technological processes. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1003136
utb.identifier.obdid 43868144
utb.identifier.scopus 2-s2.0-84874624249
utb.identifier.wok 000313767300012
utb.source d-wok
dc.date.accessioned 2013-02-24T06:51:47Z
dc.date.available 2013-02-24T06:51:47Z
dc.rights.access openAccess
utb.contributor.internalauthor Chalupa, Petr
utb.contributor.internalauthor Novák, Jakub
utb.fulltext.affiliation Petr Chalupa and Jakub Novák Department of Process Control, Faculty of Applied Informatics, Tomas Bata University in Zlin, nám. T.G. Masaryka 5555, 760 01 Zlín, Czech Republic chalupa@fai.utb.cz
utb.fulltext.dates -
utb.fulltext.sponsorship This work was supported by the Ministry of Education of the Czech Republic under grant 1M0567 and by the European Regional Development Fund under the project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089.
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