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dc.contributor.authorDittmar, Rainer
dc.date.accessioned2020-12-15T14:15:54Z
dc.date.available2020-12-15T14:15:54Z
dc.date.issued2019
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/44003
dc.description.abstractModel Predictive Control (MPC) is used to solve challenging multivariable-constrained control problems. MPC systems are successfully applied in many different branches of industry. The MPC ToolboxTM of MATLAB®/Simulink® provides powerful tools for industrial MPC application, but also for education and research at technical universities. This book gives an overview of the basic ideas and advantages of the MPC concept. It shows how MPC systems can be designed, tuned, and simulated using the MPC Toolbox. Selected process engineering benchmark examples are used to demonstrate typical design approaches and help deepen the understanding of MPC technologies. The book is aimed at engineers in industry interested in the development and application of MPC systems, as well as students of different technical disciplines seeking an introduction into this field.
dc.languageGerman
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UF Business applications::UFM Mathematical & statistical software
dc.subject.otherComputers
dc.subject.otherMathematical & Statistical Software
dc.titleModel Predictive Control mit MATLAB und Simulink
dc.title.alternativeModel Predictive Control with MATLAB and Simulink
dc.typebook
oapen.identifier.doihttps://doi.org/10.5772/intechopen.86001
oapen.relation.isPublishedByInTechOpen
virtual.oapen_relation_isPublishedBy.publisher_nameInTechOpen
virtual.oapen_relation_isPublishedBy.publisher_websitehttps://www.intechopen.com/
oapen.relation.isFundedByb818ba9d-2dd9-4fd7-a364-7f305aef7ee9
virtual.oapen_relation_isFundedBy.grantor_nameKnowledge Unlatched
oapen.relation.isbn9781839626388
oapen.collectionKnowledge Unlatched (KU)
oapen.imprintIntechOpen
oapen.identifierhttps://openresearchlibrary.org/viewer/10774e7f-1212-4d59-8a24-dc5a7c252143
oapen.identifier.isbn9781839626388
grantor.number104993


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