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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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5. ExperimentalResults is significantly larger than∆T1. It indicates that the temperaturewin- dow in PID control mainly depend on the setup and other external factors (suchasthetarget temperature),whichalsoreflect thefact that thePIDcontrollerdoesnothavetheactiveability to improvethetem- peraturedistribution. In principle, all 18 heating sources within the new CA3 could be used for the controlling, but in the above as well as following experiments, only 12 of them (the first two modules) are used. That is because for the other 6 heating sources using the low-ripple power supplies, they are not able to output power lower than10%of the maximum power. They can work properly when the control input value u(k) is larger than 0.1, but when the value is lower than 0.1, the practical output power is always fixed at 10%×2kW = 200W. This behavior would cause extra disturbances to the system estimation and it is also not re- liable considering some safety issues. Therefore in these experiments, only the first 12 heating sources are used. In the future, additional micro controllers or frequency converters will be attached to the low- ripple power supplies to make sure that they will work in a securer PWMmode. However, forPIDthenumberofheatingsourcesanddifferenttypesof power supplies do not have any severe impacts to the control perfor- mance. The control results of the PID controller in the old HEPHAIS- TOSCA3using36heatingsourcesareshowninfigure 5.24. Compar- ing the results in these two experiments, they have the similar control behaviors and the same level of final temperature windows. More heating sources does not necessarily lead to a better control perfor- manceandamorehomogeneoustemperaturedistribution. Aslongas thenumberoftheheatingsourcesisenoughtoprovideadiverseheat- ing (which depends on the specific application) and they are properly distributed spatially, the control diversity as well as the correspond- ing control performance can be guaranteed. This phenomenon is also reflected by some of the following results, and it is one of the reasons whyinthenewCA3thenumberofsources ishalved. 162
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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