Newly developed double neural network concept for reliable fast plasma position control

Neural network is considered as a parameter estimation tool in plasma contr ols for next generation tokamak such as ITER. The neural network has been r eported to be so accurate and fast for plasma equilibrium identification th at it may be applied to the control of complex tokamak plasmas. For this ap plication, the reliability of the conventional neural network needs to be i mproved. In this study, a new idea of double neural network is developed to achieve this. The new idea has been applied to simple plasma position iden tification of KSTAR tokamak for feasibility test. Characteristics of the co ncept show higher reliability and fault tolerance even in severe faulty con ditions, which may make neural network applicable to plasma control reliabl y and widely in future tokamaks. (C) 2001 American Institute of Physics.