Seite - 49 - in Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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3.2. Grey-boxModeling
−→
En,m= En,m :=
E
n,m
x
En,my
En,mz
, (3.21)
with
−→ex= ex :=
10
0
, −→ey= ey :=
01
0
, −→ez= ez :=
00
1
.
Therefore the overall superposed electric field at the location −→
En can
bereplacedbythevectorEn, suchas
En= M∑
m=1 vm ·En,m =
E
n
x
Eny
Enz
, (3.22)
where
Enx=v1E n,1
x +v2E
n,2
x + · ··+vMEn,Mx ,
Eny =v1E
n,1
y +v2E
n,2
y + · ··+vMEn,My ,
Enz =v1E
n,1
z +v2E
n,2
z + · ··+vMEn,Mz , (3.23)
and vm (1≤m≤M) is the portion of amplitude of the electric field
fromthem-th feedingsource.
Definingthenewvectorsas
V= [
v1, v2, . . ., vM ]T
,
Enx= [
En,1x ,E
n,2
x , . . .,E
n,M
x ]
,
Eny = [
En,1y ,E
n,2
y , . . .,E
n,M
y ]
,
Enz = [
En,1z ,E
n,2
z , . . .,E
n,M
z ]
, (3.24)
thecomponents in thevectorEn canbeexpressedas
Enx=E n
xV, E
n
y =E
n
yV, E
n
z =E
n
zV. (3.25)
49
To make the electric field easier to use in the following derivations, it
is rewritten inavector form,suchas
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