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3. ModelingMicrowaveHeating
termcanbefurtherwrittenas
Pcd= ∂
∂x (
κxl 2∂T
∂x )
· l+ ∂
∂y (
κyl 2∂T
∂y )
· l
= ∂
∂x (
κ ∂T
∂x )
· l3+ ∂
∂y (
κ ∂T
∂y )
· l3
=∇·(κ∇T) · l3, (3.9)
where∇ is the two-dimension differential operator. If the sign of
∇·(κ∇T) is positive, the energy goes from other parts of the load
to thiscell, andviceversa.
•Microwaveheatingpower
According to equation 2.6, the microwave heating power density
iswrittenas
pmw= 1
2 σe(T) ∥∥∥−→E∥∥∥2 , (3.10)
whereσe(T) is theelectricalconductivityoftheheatedloadattem-
perature T (equation 2.6). The electric field strength as well as
the entire EM field distribution is determined by the well-known
Maxwell’s equations [Mer98] [Y+66]. Unlike numerical simula-
tionapproaches, theexactsolutionsoftheMaxwell’sequationsare
not required for the temperature control system. Instead the mi-
crowave heating power densities are approximated and estimated
using different system identification methods that will be intro-
duced later this chapter. For a small cell as defined in figure 3.1,
it is assumed that the electric field is constant within the cell, and
correspondingly themicrowaveheatingpower isgivenby
Pmw=pmw · l3. (3.11)
Replacing the corresponding terms in equation 3.1 by above expres-
sions, thereis thecompleteheat transferequationforanylocation(cu-
44
biccell) onthesurfaceof theheated load
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Buch Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources"
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