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dc.contributor.authorDittmar, Rainer
dc.date.accessioned2025-03-08T09:16:54Z
dc.date.available2025-03-08T09:16:54Z
dc.date.issued2019
dc.date.submitted2020-12-15T14:15:54Z
dc.identifierhttps://library.oapen.org/handle/20.500.12657/44003
dc.identifier.urihttps://doab-dev.siscern.org/handle/20.500.12854/191594
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.rightsopen access
dc.subject.otherComputers
dc.subject.otherMathematical & Statistical Software
dc.subject.otherthema EDItEUR::U Computing and Information Technology::UF Business applications::UFM Mathematical and 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.isPublishedBy035ecc65-6737-43cf-a13a-6bdf67ce01f4
oapen.relation.isFundedBy969f21b5-ac00-4517-9de2-44973eec6874
oapen.relation.isbn9781839626388
oapen.collectionKnowledge Unlatched (KU)
oapen.imprintIntechOpen
dc.number104993
dc.relationisFundedByb818ba9d-2dd9-4fd7-a364-7f305aef7ee9


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