ADAPTIVE FUZZY SYNCHRONIZATION OF TWO DIFFERENT CHAOTIC SYSTEMS WITH STOCHASTIC UNKNOWN PARAMETERS

Abstract

In this paper, we present a method for synchronizing two different chaotic systems that have unknown parameters that are affected by stochastic variations generated by the Wiener process. The parameters are expressed by the sum of their mean values and the white Gaussian noise multiplied by the diffusion matrices. To describe the unknown nonlinear function yielded by Ito's lemma due to the unknown diffusion matrices, a fuzzy logic system is employed. Using adaptive fuzzy control, the response system is synchronized with the drive system within an arbitrarily small error bound. Numerical simulations show the effectiveness of the proposed method.