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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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5.3. ResultsofDifferentControlMethods Time Temperature 75°C 100°C 8°C/min Figure5.22. Illustrationof the target temperaturecurve. 0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0 3 0 0 02 0 4 0 6 0 8 0 1 0 0 1 2 0 DT2 = 1 3 . 8 ° C ~ 1 4 ° C T i m e ( s ) T a r g e tT 1T 2T 3T 4T 5 DT1 = 8 . 9 ° C ~ 9 . 1 ° C 0 2 0 4 0 6 0 8 0 1 0 0 Figure5.23. Control performance of PID control method (new cavity 3, 12 sources). are slightly smaller than the value in the beginning, that is due to the combined thermal conduction effect of the aluminum plate and the workpiece itself. The PID controller itself does not have the ability to reduce the temperature window and improve the temperature distri- bution. It should be noted that the second temperature window ∆T2 161
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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