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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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5. ExperimentalResults teflonplatetothemetaltableishigh. Butforthecornersandtheedges, due to the deformations there is no contact as well as heat exchange between the teflon plate and the metal table. The different heat dis- sipation effects between the central and other parts of the workpiece leadtothecoldarea inthecentralandhotareas inthecornersandthe edges. Thisphenomenonexistsduringtheentireheatingprocess,and it isalsonotcompensatableusingdifferentcontrolmethods. Good contact Deformation Figure5.20. Deformationof the teflonplate (nocontactbetweentheplateand metal table). Based on above observations, a simple and straightforward way to maintainagoodcontrollabilityofthesystemistoreducethesizeofthe heated workpiece. The disturbance caused by different heat conduc- tion effects of the tool is less severe for a small-tool setup, compared with the case in figure 5.17. As a result, the corresponding tempera- ture distribution of the workpiece can be controlled using aforemen- tioned control methods. Therefore a smaller setup, where the surface areas of both the workpiece and the aluminum plate are reduced into approximately0.5m×0.5m, isused in followingexperiments. 158
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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
Title
Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
Author
Yiming Sun
Publisher
KIT Scientific Publishing
Location
Karlsruhe
Date
2016
Language
English
License
CC BY-SA 3.0
ISBN
978-3-7315-0467-2
Size
14.8 x 21.0 cm
Pages
260
Keywords
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