Seite - 45 - in 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
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
- Kategorie
- Technik