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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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σ′ Stefan-Boltzmannconstant W/ ( m2 ·K4) h Convectionheat transfer coefficient W/ ( m2 ·K) % Emissivityof thesurfaceof the heated load unitless In the mathematical modeling and control parts (chapter 3 and 4), scalars are represented by non-bold symbols. Vectors are represented by bold symbols, and matrices are represented by bold symbols with brackets. l Lengthofunit cell m pcd Dissipated/heatingpowerdensity byconduction W/m3 pcv Dissipatedpowerdensityby convection W/m2 prd Dissipatedpowerdensityby radiation W/m2 pmw Microwaveheatingpowerdensity W/m3 Pcd Dissipated/heatingpowerby conduction W Pcv Dissipatedpowerbyconvection W Prd Dissipatedpowerbyradiation W Pmw Microwaveheatingpower W Ta Ambient temperature K Y Temperaturedifferencebetween the loadandambientair K T Temperaturevectorof theheated load K Y Temperaturedifferencevector K U Powerportionvector unitless V Amplitudeportionvector unitless P Dissipated/heatingpowervector unitless v ListofSymbols
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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