Estimation of Plasma Boundary in ITER Configuration by Means of Soft Computing Approach

M. Versaci, F.C. Morabito, S. Calcagno, and A. Greco (Italy)


Neural Networks, Identification Problems


Concerning the control of plasma column evolution in ITER machine, the reconstruction of the plasma shape in the reactor is one important step. In this paper a soft computing approach to estimate the distances of the plasma boundary from the first wall of the vacuum vessel is carried out by means of Neural Networks. Starting from magnetic measurements, Neural Networks are exploited in order to reconstruct the plasma shape. In order to reduce the computational complexity, a non linear technique for ranking sensor is presented

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