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Published by LAP LAMBERT Academic Publishing Apr 2015, 2015
ISBN 10: 3659440515 ISBN 13: 9783659440519
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book addresses the issue of Model Predictive Control (MPC), supported by a real life application of temperature control in plate heat exchangers, as it is noticed that classical control strategies, for instance PI and PID, often give a relatively large variance in temperature. This results in the producer having to set up a higher control temperature set point than the actual needed one, which introduces energy loss as well as affecting sometimes the treated product itself. One way of reducing temperature variance in order to be able to lower the temperature set-point without re-designing the plant, is to introduce better control. Model Predictive Control (MPC) is proposed as a control alternative. Such a control philosophy requires an internal model of the process, which is used to predict future process behavior. A survey of different MPC techniques is given, highlighting the two most popular linear MPC algorithms, for instance Predictive Functional Control (PFC) and Generalised Predictive Control (GPC) being evaluated for the case study. 424 pp. Englisch.
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Published by LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659440515 ISBN 13: 9783659440519
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Khadir Mohamed TarekPr. Khadir Mohamed Tarek was born in 1972 in Annaba Algeria, he obtained his Engineering Degree in 1995, then a M.Eng from DCU, Ireland and a Ph.D in control engineering from NUI Maynooth, Ireland. Pr. John Ringwo.
Language: English
Published by LAP LAMBERT Academic Publishing Apr 2015, 2015
ISBN 10: 3659440515 ISBN 13: 9783659440519
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book addresses the issue of Model Predictive Control (MPC), supported by a real life application of temperature control in plate heat exchangers, as it is noticed that classical control strategies, for instance PI and PID, often give a relatively large variance in temperature. This results in the producer having to set up a higher control temperature set point than the actual needed one, which introduces energy loss as well as affecting sometimes the treated product itself. One way of reducing temperature variance in order to be able to lower the temperature set-point without re-designing the plant, is to introduce better control. Model Predictive Control (MPC) is proposed as a control alternative. Such a control philosophy requires an internal model of the process, which is used to predict future process behavior. A survey of different MPC techniques is given, highlighting the two most popular linear MPC algorithms, for instance Predictive Functional Control (PFC) and Generalised Predictive Control (GPC) being evaluated for the case study.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 424 pp. Englisch.
Language: English
Published by LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659440515 ISBN 13: 9783659440519
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book addresses the issue of Model Predictive Control (MPC), supported by a real life application of temperature control in plate heat exchangers, as it is noticed that classical control strategies, for instance PI and PID, often give a relatively large variance in temperature. This results in the producer having to set up a higher control temperature set point than the actual needed one, which introduces energy loss as well as affecting sometimes the treated product itself. One way of reducing temperature variance in order to be able to lower the temperature set-point without re-designing the plant, is to introduce better control. Model Predictive Control (MPC) is proposed as a control alternative. Such a control philosophy requires an internal model of the process, which is used to predict future process behavior. A survey of different MPC techniques is given, highlighting the two most popular linear MPC algorithms, for instance Predictive Functional Control (PFC) and Generalised Predictive Control (GPC) being evaluated for the case study.