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4.1. AdaptiveControl
Πd= 




 [IM] [OM] . .. [OM]
[IM] [IM] . .. [OM]
... ... ... ...
[IM] [IM] . .. [IM] 




 ,
where [IM]and [OM]are identicalandzeromatrices (M×M), respec-
tively. Thedimensionsof [Id] isMp×M andthedimensionof [Πd] is
Mp×Mp. Using the above notations, the control constraint in equa-
tion 4.4 isconverted into
−[Πd]−1 [Id]U(k−1)≤ ∆Ud(k) ≤ [Πd]−1 ( 1− [Id]U(k−1) )
,
(4.17)
where1 isanall-onesvector (Mp×1) as
1= [
1, 1, 1, . . .,
1︸
︷︷ ︸
Mp ]T
.
Theoriginalcontrol task(equation 4.15)canbedescribedbyaregular
quadraticprogramming(QP)problem[GM86]
minJLM(k) = min [
∆UTd(k) (
[Ξd(k)]
T
[Γ] [Ξd(k)]+[Λ] )
∆Ud(k)
−2∆UTd(k)[Ξd(k)]T [Γ] (
Yd,t(k)− [Fd(k)]Xd(k) ))
+
(
Yd,t(k)− [Fd(k)]Xd(k)
)T
Γ
(
Yd,t(k)− [Fd(k)]Xd(k)
)]
,
(4.18)
subject to
−[Πd]−1 [Id]U(k−1)≤ ∆Ud(k) ≤ [Πd]−1 ( 1− [Id]U(k−1) )
,
The above QP problem can be solved using different numerical meth-
ods [Wan09]. In the practical MPC system of HEPHAISTOS, the con-
trolsolutionisfirstlycalculatedusingthestandardDMCalgorithm. If
theresultedcontrolvectorU(k) iswithinthecontrolconstraint, itwill
be directly implemented. Otherwise, the control task will be trans-
ferred into the QP problem (equation 4.18) and solved using the nu-
mericalmethod.
95
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book Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources"
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
- Category
- Technik