Seite - 34 - in Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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2. IntroductionofHEPHAISTOS
3 0
4 0
3 0
4 0
3 0
4 5
3 0
4 5
0 1 0 0 2 0 0 3 0
00
2 0
4 0 T 1 f r o m F O S
T 2 f r o m F O S
T 1 f r o m I R C
T 2 f r o m I R C
T i m e ( s )
P o w e r
Figure2.17. Comparison of measurement delays using the fiber optic sensor
(FOS)andthe infraredcamera (IRC).
difficulties toboththecontrolof thesystemandthetemperaturemea-
surement. There is no way to eliminate or reduce its influences from
neitherhardwarenormodelingaspects.
The above mentioned problems of thermocouples and fiber optic sen-
sors can be easily overcome by the infrared camera. The temperature
measurementusingtheinfraredcameraiscontactless,anditcanbedi-
rectlyimplementedwithoutanyadditionalprocessing. Asalsoshown
in figure 2.17, the time delay of the infrared camera is so small that
canbeneglectedinpractice. Theonlydifficultyregardingtheinfrared
camera is the temperaturemismatchcausedbythemetallicmeshthat
isput inbetweenthecameraandthecavity.
34
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