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4.1. AdaptiveControl
smaller than 1. Another simpler method is to randomly choose
∆i(k) to be either 1 or -1. Different methods of determining ∆i(k)
canbeappliedaccordingly.
• In the standard SPSA control system, one complete weight update
of w(k) takes three control periods. In the beginning time k, the
NN controller generates ∆(k),w(±)(k) and U(±)(k). and imple-
ments the new control action U(+)(k). At timek+1, it measures
correspondingsystemoutputY(+)(k) (whichisalsoY(k+1)), cal-
culates the first evaluation valueJ(+)(k) using Y(+)(k), and then
implements U(−)(k). The same procedures are repeated at time
k+2 to calculateJ(−)(k). After that the weight w(k) will be up-
dated using equation 4.25. The resulted new weight is not strictly
w(k+1), butw(k+3)whichwillbeusedtocalculatenewcontrol
action for the periodk+3. In principle, the output sequence can
beexpressedas (seefigure 4.5)
O= {. .. ,Y(k),Y(+)(k),Y(−)(k),
Y(k+3),Y(+)(k+3),Y(−)(k+3), .. .}. (4.28)
k k+1 k+5k+2 Time
U(k)
k+3 k+4
Y(k) Y+(k) Y-(k) Y+(k+3)
Y-(k+3)Y(k+3)
U+(k)
U-(k) U(k+3) U
+(k+3)
U-(k+3)
update of weights update of weights
Figure4.5. Weightsupdate in thestandardSPSAalgorithm.
The standard SPSA algorithm (equation 4.26) has a critical limita-
tion that makes it difficult to be realized in practice. It is defined
105
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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
- Category
- Technik