Seite - 52 - in Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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3. ModelingMicrowaveHeating
thenequation 3.32 is further transferred into
dYn
dt = Anc(t) ·Yn+Bnc(t)U(t). (3.34)
Basedonthissingleoutputmodel,acontinuous-timeMIMOmodel is
builtas
dY
dt = [Ac(t)]Y+[Bc(t)]U(t), (3.35)
whereY is theoutputvectordefinedas
Y = [
Y1,Y2, .. . ,YN ]T
, (3.36)
andthestatematrixandtheoutputmatrixaredefinedas
[Ac(t)] :=
A1c(t) 0 · ·· 0
0 A2c(t) · ·· 0
... ... ... ...
0 0 · ·· ANc (t)
,
[Bc(t)] :=
B1,1c (t) B 1,2
c (t) · ·· B1,Mc (t)
B2,1c (t) B 2,2
c (t) · ·· B2,Mc (t)
... ... ... ...
BN,1c (t) B N,2
c (t) · ·· BN,Mc (t)
. (3.37)
Beforeabovemodelscanbeusedinrealcontrollerdesign, thelaststep
is discretization, because in practice the controller is always operated
indiscrete-time. Differentdiscretizationmethodsexistandinthisdis-
sertationtheEulermethod[Lju98]isapplied. Whenthesamplingtime
∆t is a sufficiently small constant (1.5 s or even less), the temperature
changing rate on the left-hand side of equation 3.35 can be approxi-
matedby
dY
dt ≈ 1
∆t (
Y(k+1)−Y(k) )
,
wherek indicates thediscrete timeinterval.
52
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