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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. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive fuzzy synchronization control strategy for a class of different uncertain fractional-order chaotic/hyperchaotic systems with unknown external disturbances via T-S fuzzy systems, where the parallel distributed compensation technology is provided to design adaptive controller with fractional adaptation laws. T-S fuzzy models are employed to approximate the unknown nonlinear systems and tracking error signals are used to update the parametric estimates. The asymptotic stability of the closed-loop system and the boundedness of the states and parameters are guaranteed by fractional Lyapunov theory. This approach is also valid for synchronization of fractional-order chaotic systems with the same system structure. One constructive example is given to verify the feasibility and superiority of the proposed method. [ABSTRACT FROM AUTHOR]