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Microwave heating provides an energy effi cient and
promising alternative to conventional industrial heating
approaches. Microwave heating has the volumetric heat-
ing capability, which means it penetrates into the object.
Surface and interior can be heated simultaneously. Com-
pared with convectional heating both, process time and
energy consumption can be signifi cantly reduced using
microwave heating. However, the non-uniform tempera-
ture distribution is always an issue that limits the imple-
mentation of microwave heating in industry applications.
In order to improve the temperature homogeneity and
enhance the applicability of microwave heating, an inno-
vative real-time microwave control technique is proposed
in this work. Different control structures have been devel-
oped and compared, to automatically adjust the power
levels of spatially distributed microwave feeding anten-
nas. By doing that, the electromagnetic (EM) fi eld within
the microwave chamber will be actively optimized, and
hence, the corresponding temperature distribution will
be improved.
Yiming Sun graduated from the University of Bremen in
2012 in the fi eld of Communication and Information Tech-
nology. In 2012 he joined the Institute for Pulsed Power
and Microwave Technology (IHM) as Ph.D. candidate and
the Institute for Data Processing and Electronics (IPE) as
research assistant at the Karlsruhe Institute of Technology
(KIT). In 2015 he fi nished his doctoral dissertation with
distinction. His major research interests are electromag-
netic theory, control system design, mathematical mod-
eling and machine learning.
ISSN 2192-2764
ISBN 978-3-7315-0467-2
Karlsruher Forschungsberichte aus dem
Institut für Hochleistungsimpuls- und Mikrowellentechnik
Herausgeber: Prof. Dr.-Ing. John Jelonnek
9 783731 504672
ISBN 978-3-7315-0467-2
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
- Kategorie
- Technik