Controlling the Multi-Scroll Chaotic Attractors Using a Fuzzy Neural Networks Compensator

In this paper controlling multi-scroll chaotic attractors from a saturated function series is studied. For many chaotic systems that can be decomposed into a sum of a linear and nonlinear part, under some mild conditions fuzzy neural networks (FNNs) can be used to well approximate the nonlinear part of the system dynamics. The resulting system is then dominated by the linear part, with some small or weak residual nonlinearity due to the FNN approximation errors. Thus, a simple linear state feedback controller can be proposed to drive the multi-scroll chaotic attractors to the desired targets or periodic trajectory. In addition to some theoretical analysis, computer simulations on multi-scroll chaotic attractors are presented to demonstrate the effectiveness of the proposed control scheme.