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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
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
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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources