Neural Networks Synchronization For Uncertain Fractional-order Nonlinear Chaotic Systems With Input Saturation

Chaos is a kind of complex nonlinear motion,and it has a potential application value in the field of secure communication,signal propagation and control engineer-ing,which making chaotic system synchronization control research become a popular research topic for home and foreign scholars.In recent years,many scholars have studied the integer-order systems with input saturation with the continuous research on the synchronization problem of fractional-order nonlinear chaotic systems.But so far,there is little literature studying the control and synchronization problem of the fractional-order nonlinear chaotic systems with input saturation.This paper mainly studies the synchronization problem of fractional-order chaotic systems with input saturation.It is divided into four chapters,the specific structure is as follows:Chapter 1,preliminaries,introduces the definition and properties of fractional calculus to be used in this paper and some concepts and results of neural networks.Chapter 2,synchronization controller design,a fractional-order adaptive con-troller is designed based on the neural networks adaptive control algorithm.And the nonlinear function of the system is estimated by RBF neural networks.Chapter 3,stability analysis,the fractional-order adaptive laws are constructed based on the fractional Lyapunov stability theory and all the variables in the closed-loop system are proved bounded.Chapter 4,numerical simulation,the validity of the method is proved by the synchronization of fractional chaotic systems with different structures.