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5.1. Verification inHEPHAISTOS
cal. Thesameresultsarealsoreflectedbytheheatingratesas infigure
5.5.
1 2 3 4
50
.0
0 .1
0 .2
0 .3
0 .4
0 .5
0 .6
0 .7
0 .8
I n d e x o f m e a s u r e d p o i n t s
T r i a l 1 T r i a l 2 T r i a l 3
Figure5.5. Heatingratescomparisonof3 trialsduringthefirst twoseconds.
The heating rates shown in figure 5.5 are calculated using the follow-
ingequation
R= 1
∆t ( Y(k+1)−A(k)Y(k)) ∝ Pmw. (5.1)
Since the heating rates are directly proportional to the microwave
heating power, therefore they can be used as representatives of the
heatingpower. Inotherwords, if theheatingratesofdifferentsources
follow the scalar addition rule, it means the heating power also fol-
lows the scalar addition rule. This principle will be used later in the
thirdstepof theverification.
Step2: Heatingpatternsofmultiplefeedingsources
The second step is to test the heating stability of multiple feeding
sources. The proceduresused in this setupis thesame asdescribed in
figure 5.2, except the objective is switched to different combinations
137
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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