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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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5. ExperimentalResults In this chapter, the results of practical experiments will be presented. In the beginning, a number of preliminary trials are performed in or- der toverifythevalidityof the linearandthenonlinearmodels (given bytheequation 3.41and 3.46respectively). Thenthesystemidentifi- cationalgorithmsintroducedinchapter 3aretestedandcompared, to identify themostappropriatesystemidentificationmethodforpracti- cal heating experiments. In the end, both the adaptive and the intelli- gent control methods are applied, and the corresponding experimen- tal resultsarepresentedandcompared. 5.1. VerificationinHEPHAISTOS Due to its complicated structure, some fundamental characteristics of HEPHAISTOS are difficult to determine theoretically, e.g. the proper- ties of the EM field distributions. In order to understand the capabili- tiesandlimitsoftheHEPHAISTOSsystembetter,anumberofprelim- inary tests have been done with respect to one fundamental question, which is thepracticalpowersuperpositionprinciple. According to the introductions in chapter 3, there are two different powersuperpositionprinciples,definedasthescalaradditionandthe vector addition principles. These two principles are the basis of the linear 3.41 and the nonlinear 3.46 state-space models, respectively, which are also the foundations of the entire MPC system. From this pointofview,toverifythepowersuperpositionprincipleisequivalent to theverificationofvaliditiesof these twogrey-boxmodels. The entire verification procedures contain three aspects. The first as- pect is to check if each individual feeding source can provide a sta- ble heating pattern. For each microwave source of HEPHAISTOS, 133
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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