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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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3. ModelingMicrowaveHeating For instance, a rectangular dielectric foil is heated to 350 K, and the temperature of surrounding air is 300 K. For the dielectric materi- als, it is assumed the corresponding heat conductivities are below 10 W/(m ·K). For example, the conductivity of silicon rubber (the mate- rial that ismostlyusedinourexperiments) isbetween0.2W/(m·K) to 1.3 W/(m ·K) [Sil12], and the conductivity of CFRP using epoxy ma- trices is 5W/(m ·K) to 7W/(m ·K) in plane [Tia11]. The second spa- tial derivative of the temperature is difficult to be defined. Based on themoderatelyhomogeneousEMfielddistributionwithinHEPHAIS- TOS, it is feasible to use±0.1K/cm2 as the second spatial derivatives. Otherparametersareassumedas %= 0.9, h=20W/(m2 ·K), Using above values, for a simple cell on the surface (1 cm×1 cm×1 mm)theratesof thermalconduction, convectionandradiationcanbe calculatedas ∣∣Pcd∣∣<0.01W, Pcv= −0.1W, Prd= −0.035W. (3.14) Above results show that the dissipated power of either thermal con- vection or thermal radiation is much larger than that of thermal con- duction, therefore the thermal conduction term in equation 3.13 can be omitted. Furthermore, the dissipated power of both thermal con- vectionandthermalradiationareproportional tothetemperaturedif- ferenceT−Ta and the area of the unit cell l2. In this case, the overall dissipatedpower is rewrittenas Pdiss≈Pcv +Prd ≈ − h˜(T)(T−Ta) · l2, h˜(T) :=h+%σ′(T2+T2a) ·(T+Ta), (3.15) where h˜(T) isdefinedas theoverallpowerdissipationcoefficient that contains effects of both thermal convection and thermal radiation. Substituting the above equation 3.15 into equation 3.12, the resulted system models has a similar ARMAX form like the models used in [RCVI99]and[SBA00]. 46
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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
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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources