Robust adaptive control of fractional-order memristive neural networks

Abstract This chapter is about the synchronization of fractional-order memristive neural networks. At first, some basic concepts of fractional calculus are presented, and the model of fractional-order memristive neural networks is described. Then a robust adaptive controller is designed for the synchronization of these systems. The proposed robust adaptive control strategy is an efficient method for the synchronization of complex uncertain systems. It is supposed that the dynamics of the slave and master system are fully unknown. The adaption mechanism is designed to adjust the parameters of the controller. By using a proper sliding surface, during the control procedure, the parameters of the control scheme are updated. The stability of the proposed method is proven. Finally, the simulation results, which show the effective performance of the proposed method, are illustrated.