Synchronization of Uncertain Perturbed Chaotic Neural Network Using Tracking Differential Observer

In this paper, the problem of chaos synchronization between the master chaotic neural network and the slave network is investigated. The parameters of the master system is completely unknown and the system is perturbed by external disturbances. First, a simple observer based on tracking differentiator is designed to estimate all the nonlinearities, unknown system functions and disturbances. Then, appropriate controller with dynamic active compensating characteristics is proposed. Subsequently, based on the singular perturbation theory, the control method can guarantee the stable of the error dynamic system. Two illustrative examples are presented to verify the effectiveness of the proposed technique.