Neural network synchronization of fractional-order chaotic systems subject to backlash nonlinearity

Abstract

This paper investigates the neural network (NN) synchronization controller design problem of fractional-order chaotic systems (FOCSs) subject to disturbances and backlash-like hysteresis input. First, we divide the backlash-like hysteresis input into two parts, one of which is the actual controller and the other that can be approximated by NNs. Then, an adaptive NN synchronization control input is implemented to drive the synchronization error between two identical FOCSs into a small domain. Finally, the effect of our approach is indicated by simulation results.