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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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5.3. ResultsofDifferentControlMethods lar, which lead to the same level of heat dissipation rates at different parts of the workpiece. Therefore the hot spots in the central part of theworkpiecewouldbeeliminated,whichhasbeenconfirmedbythe experimental results suchasshowninfigure 5.19. (a) t=5min. (b) t=10min. (c) t=15min. (d) t=20min. Figure5.19. Heatingprocess ( from(a) to (d) )with thesetupof teflonplate. Although the hot spots are removed, there is another problem oc- curred due to the heat dissipation from the teflon plate to the metal table. When the workpiece is heated to a high temperature, the tem- peratureof theteflonplate isalsohigh,whichcausesdeformationson the edges (see figures 5.20). For the central part of the plate, it has di- rectcontactwiththemetal tableandtheheatdissipationrate fromthe 157
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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
Titel
Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
Autor
Yiming Sun
Verlag
KIT Scientific Publishing
Ort
Karlsruhe
Datum
2016
Sprache
englisch
Lizenz
CC BY-SA 3.0
ISBN
978-3-7315-0467-2
Abmessungen
14.8 x 21.0 cm
Seiten
260
Schlagwörter
Mikrowellenerwärmung, Mehrgrößenregelung, Modellprädiktive Regelung, Künstliches neuronales Netz, Bestärkendes Lernenmicrowave heating, multiple-input multiple-output (MIMO), model predictive control (MPC), neural network, reinforcement learning
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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources