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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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3.2. Grey-boxModeling Pab︷ ︸︸ ︷ ρcp dT dt · l3= Pcd︷ ︸︸ ︷ ∇·(κ∇T) · l3 Pcv︷ ︸︸ ︷ −h(T−Ta) · l2 Prd︷ ︸︸ ︷ −%σ′(T4−T4a) · l2 + 1 2 σe(T) ∥∥∥−→E∥∥∥2 · l3︸ ︷︷ ︸ Pmw . (3.12) It shouldbenotedthat in theaboveequationthepowerabsorptionor dissipation isalreadyreflectedbythesignof individual terms. 3.2.2. ApproximationandSimplification Theaboveequation 3.12isacomplicatedparabolicpartialdifferential equation (PDE). This equation can be only solved in special cases like the one-dimensional scenario. For a microwave heating system like HEPHAISTOS, where the electromagnetic field distribution is com- plex and varying all the time during the heating, a general solution is impossible tobeobtained. Inorder tomakeequation 3.12suitable for a control system, approximation and simplification have to be done here, regardingdifferent termsontheright-handside. Approximationsof thethermodynamic terms From equation 3.12, the overall dissipated power can be deduced, suchas Pdiss =Pcd +Pcv +Prd =∇·(κ∇T) · l3−h(T−Ta) · l2−%σ′(T4−T4a) · l2, (3.13) where thethree termsontheright-handsidecorrespondtothepower ofconduction,convectionandradiation, respectively. Averyeffective scheme to approximate this heat loss part is to ignore the rate of con- duction and only keep the rate of convection and radiation, because the effect of conduction is quantitatively much smaller than the effect of theconvectionor theradiation. 45
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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