  In order to identify complicated systems, more prominent and promising
methods are needed among which we may refer to fractional order differential
equations. The aim of this paper is to propose a fractional order nonlinear
model to predict the vertical position of a plasma column system in a Tokamak
by using real data from Damavand Tokamak. The system is identified based on a
newly introduced fractional order dynamic neural network. The proposed
fractional order dynamic neural network (FODNN) is an extension of the integer
order dynamic neural network that employs the so called fractional-order
operators. FODNN is implemented and comparison of the numerical simulation
results with experimental results shows that performance of the proposed method
by using fractional order neural network is preferred to the integer neural
network.
