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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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2. IntroductionofHEPHAISTOS tion altering of the external electric field is so high that the dipole re-orientation fails to follow. As a consequence the friction becomes smallerandthegeneratedheat isalso less. External electric field E + - - + - + - Dielectric material + - + - + - + Dipole Figure2.2. Dipolepolarizationofdielectric. The above interpretation was firstly formulated by the physicist Peter Debye [Aru10], using the well-known complex permittivity equation [GC99], suchas ε(ω) =ε′(ω)− jε′′(ω) =ε∞+ εs−ε∞ 1+jωτ , (2.2) where ε(ω) is the complex permittivity of a dielectric as a function of angular frequencyω = 2pif, ε′(ω) and ε′′(ω) are the real and imagi- nary part of ε(ω) respectively. The parameter εs is the permittivity of the material at low frequencies, ε∞ is the permittivity of the material at very high frequencies. The relaxation time τ represents the time of form and decay of the polarization within the dielectric when the externalelectricfield isappliedandvanishedrespectively. Fromtheaboveequation, it canbederivedthat ε′=ε∞+ εs−ε∞ 1+(ωτ) 2 , ε′′= ωτ (εs−ε∞) 1+(ωτ) 2 . (2.3) 18
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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