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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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3. ModelingMicrowaveHeating termcanbefurtherwrittenas Pcd= ∂ ∂x ( κxl 2∂T ∂x ) · l+ ∂ ∂y ( κyl 2∂T ∂y ) · l = ∂ ∂x ( κ ∂T ∂x ) · l3+ ∂ ∂y ( κ ∂T ∂y ) · l3 =∇·(κ∇T) · l3, (3.9) where∇ is the two-dimension differential operator. If the sign of ∇·(κ∇T) is positive, the energy goes from other parts of the load to thiscell, andviceversa. •Microwaveheatingpower According to equation 2.6, the microwave heating power density iswrittenas pmw= 1 2 σe(T) ∥∥∥−→E∥∥∥2 , (3.10) whereσe(T) is theelectricalconductivityoftheheatedloadattem- perature T (equation 2.6). The electric field strength as well as the entire EM field distribution is determined by the well-known Maxwell’s equations [Mer98] [Y+66]. Unlike numerical simula- tionapproaches, theexactsolutionsoftheMaxwell’sequationsare not required for the temperature control system. Instead the mi- crowave heating power densities are approximated and estimated using different system identification methods that will be intro- duced later this chapter. For a small cell as defined in figure 3.1, it is assumed that the electric field is constant within the cell, and correspondingly themicrowaveheatingpower isgivenby Pmw=pmw · l3. (3.11) Replacing the corresponding terms in equation 3.1 by above expres- sions, thereis thecompleteheat transferequationforanylocation(cu- 44 biccell) onthesurfaceof theheated load
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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