Seite - 159 - in Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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5.3. ResultsofDifferentControlMethods
5.3.1. PerformanceofAdaptiveControlMethods
In this part, four control methods have been tested and compared in
the new HEPHAISTOS cavity 3 (new CA3, total 18 heating sources),
including the PID control, the linear and the nonlinear MPC methods
and the SPSA based NNC method. The PID control method is used
as a benchmark for all other control methods. In the PID controller,
only one temperature can be controlled and normally the maximum
temperature is selected. The PID controller will calculate the control
inputvalueaccordingto the followingequation[ACL05]
u(k) =Kp ·e(k)+Ki · k∑
i=0 e(i)+Kd · e(k)−e(k−1)
∆t ,
e(k) =Yt(k)−Y(k), (5.2)
where e(k) is the difference between the target temperature and the
selectedtemperaturevalue. ThecoefficientKp,Ki,Kdare thepropor-
tional gain, the integral gain and the derivative gain, respectively. All
control input elementui(k) in the control vector U(k) take the same
valueasu(k).
Thesamesetupasshowninfigure 5.1isusedastheheatedworkpiece
(0.5m×0.5m), and temperatures of five different locations are mea-
sured by the infrared camera and controlled, such as in figure 5.21.
The silicone rubber setup is used instead of real CFRP material in the
experiments. In principle the control methods introduced in this dis-
sertation can be applied to all different kinds of materials. For dif-
ferent materials, the control performance would be different, and the
final controlled temperature distribution mainly depends on the ther-
mal conductivity of the setup or material. The thermal conductivity
directly determines the accuracy of the estimated model and the ef-
fective control diversity. From this point of view, the silicone rubber
setup is a good experiment material, because it has a similar thermal
conductivity with certain CFRP materials, e.g. the thermal conductiv-
ity of silicone rubber is 0.2W/(m ·K)∼ 1.3W/(m ·K) [Sil12], and the
thermalconductivityofatypicalCFRPepoxyprepregis0.6W/(m·K)
[AD10]. If the control methods can perform well using the silicone
159
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