DocumentCode :
1535436
Title :
Improvement of filamentary plasma identification via neural networks
Author :
Formisano, Alessandro ; Martone, Raffaele
Author_Institution :
Dipt. di Ingegneria dell´´Inf., Seconda Univ. di Napoli, Italy
Volume :
37
Issue :
5
fYear :
2001
fDate :
9/1/2001 12:00:00 AM
Firstpage :
3727
Lastpage :
3731
Abstract :
The identification of plasma shape and position for control purposes in thermonuclear fusion devices is usually performed via external magnetic measurements. The result should be available in a few ms to guarantee an effective control action. Fast solution of such inverse problem can be achieved via Equivalent Currents (EC) method or Artificial Neural Networks (ANN). Anyway, in the case of EC, their location become critical during the dynamical evolution of the fusion event. ANN may be beneficial in optimally locating, in real time, the EC for various plasma configurations
Keywords :
Tokamak devices; identification; inverse problems; neural nets; plasma diagnostics; Tokamak; artificial neural network; equivalent currents method; filamentary plasma identification; inverse problem; magnetic measurement; plasma control; plasma position; plasma shape; thermonuclear fusion device; Artificial neural networks; Fusion reactors; Magnetic field measurement; Magnetic flux; Magnetosphere; Neural networks; Plasma applications; Plasma devices; Plasma measurements; Plasma properties;
fLanguage :
English
Journal_Title :
Magnetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9464
Type :
jour
DOI :
10.1109/20.952700
Filename :
952700
Link To Document :
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