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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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5. ExperimentalResults whenever it isswitchedon, thefrequencyandphaseof theoutputmi- crowave is not fixed. If there is no stable heating pattern from each source, the whole microwave heating system will become a highly stochastic system where the future temperature is not predictable by neitherof the twomodels. If a stable heating pattern from each source can be guaranteed, the second part is to see if the combinations of any two or more feed- ing sources can provide stable heating patterns. This is important for the modeling. Because in practice when multiple feeding sources are switched on at the same time, unexpected coupling effects will occur between different sources. It is possible that when multiple sources areswitchedonsimultaneously, theresultingsuperposedheatingpat- terns differ a lot from time to time, which could also make the system identification process more difficult and the models unreliable. After the first two aspects are confirmed, the last part of the validation is to verify that if the scalar and the vector addition principles are able to describe thepowersuperpositionscorrectly. The setup used in the validations is shown as in figure 5.1. The tem- peraturedistributionof this setupwasmonitoredbyaninfraredcam- era in real time. All following experiments were done at the same temperature range (30◦C∼ 32◦C) and the temperature of surround- ing air was also the same (19◦C∼ 21◦C), therefore all temperature- dependentparameterscanbeconsideredasconstants. (a) y x.z Sealant Vacuum Bagging Film Thermo-electrical Foil Vacuum Hose Silicone Rubber Foil Aluminum Plate (b) Figure5.1. Thesetupusedinverificationexperiments. 134
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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