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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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2.2. StructureofHEPHAISTOS the same resonant cavity, and finally absorbed by the heat load. The functionsof individualpartsareexplainedin the following. Heated load Microwave generator Microwave cavity Waveguide Microwaves Figure2.7. Structuresofanormalmicrowaveheatingsystem. MicrowaveGenerator A microwave generator is comprised of a power supply system and a microwave source. The power supply system provides the electrical energy to the microwave source, and the microwave source uses the electrical energy to generate microwaves and propagate them further to thesucceededequipments. There are mainly two types of microwave sources, which are mi- crowave tubes (vacuum devices) and solid-state devices. Microwave tubes are the most basic and fundamental microwave sources. There are many different types of microwave tubes, such as klystrons, mag- netrons, gyrotrons and traveling-wave tubes [Jon98]. Microwave tubes have been widely used in various industrial applications, es- pecially for those requiring high power or high frequencies [Poz09]. Compared with microwave tubes, solid-state devices normally have smaller size, lighter weight and smaller frequency shifts. The main limits of solid-state devices are that they could not generate mi- crowaves of high power or high frequencies. Therefore solid-state de- vices are mainly applied for low to moderate powers at low to mod- eratefrequencies. Theaverageoutputpowerversusfrequencyperfor- mance of the microwave tubes and the solid-state devices is shown in figure 2.8. 23
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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