A neural network approach for the detection of the locking position in RFX

Author

Barana, O. ; Manduchi, G. ; Serri, A. ; Sonato, P.

Author_Institution

Consorzio RFX, Padova, Italy

fYear

1999

fDate

1999

Firstpage

575

Lastpage

578

Abstract

Recently in RFX, where wall locked modes were always present, a new technique has demonstrated the possibility to induce a continuous rotation of the modes with respect to the wall. In this technique the nonlinear coupling of the m=0 and m=1 modes has been used to decouple the modes themselves. In the present experiments the mode rotation is induced with a preprogrammed waveform of a toroidal magnetic field rotating ripple. A feedback system able to create a continuous rotation with variable and increasing speed is now under implementation. A neural network (NN) has been developed to identify the locked mode position. In the paper different NNs are presented, discussed and compared

Keywords

feedback; fusion reactor design; neural nets; nuclear engineering computing; plasma flow; plasma instability; plasma-wall interactions; reversed field pinch; RFX; Reversed Field Experiment; continuous rotation; feedback system; fusion reactors; locking position detection; neural network approach; nonlinear coupling; preprogrammed waveform; toroidal magnetic field rotating ripple; wall locked modes; Feedback; Intelligent networks; Laser mode locking; Magnetic variables control; Neural networks; Neurofeedback; Plasma properties; Tokamaks; Toroidal magnetic fields; Torque;

fLanguage

English

Publisher

ieee

Conference_Titel

Fusion Engineering, 1999. 18th Symposium on

Conference_Location

Albuquerque, NM

Print_ISBN

0-7803-5829-5

Type

conf

DOI

10.1109/FUSION.1999.849905

Filename

849905