Seite - 180 - in Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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5. ExperimentalResults
0 3 0 0 6 0 0 9 0 0 1 2 0 0 1 5 0
02
0
4 0
6 0
8 0
DT =1 1 . 8
°C
~ 1 2 . 5 ° C DT =4 . 2 ° C ~ 6 . 5
°C
T i m e ( s ) T a r g e
tT
m a
xT
m i n
0
2 0
4 0
6 0
8 0
1 0 0
(b)Thesecondtrial (usingthesamecontroller trainedfromthefirst trial).
0 2 5 0 5 0 0 7 5 0 1 0 0
02
0
4 0
6 0
8 0
DT =5 °C ~ 6 . 5 ° C
T i m e ( s ) T a r g e
tT
m a
xT
m i n
0
2 0
4 0
6 0
8 0
1 0 0
(c) The third trial (usingthesamecontroller trainedfromthesecondtrial).
Figure5.37. Control results of theQ(λ)based RLC method in three consecu-
tive trials.
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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