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Go to Editorial ManagerThis paper is concerned with performance on the widely used control technique: adaptive control for synchronization between two identical chaotic systems embedded in the Master and Slave. It is assumed that the parameters of slave system are unknown. The required stability condition is derived to ensure the stability of error dynamics. Adaptive control laws are designed using appropriate parameters estimation law. The system parameters are asymptotically synchronized; thus the slave parameters can be identified. As an application, the proposed scheme is applied to secure communication system. The information signal is transmitted and recovered on the basis of identification parameters also the system is tested under the consideration of the noisy channel. Finally, through Numerical simulation results, the proposed scheme was success in the communication application.
In this paper, a neuro-fuzzy network-based adaptive tracking controller is suggested for controlling a type of nonlinear system. Where two neuro-fuzzy networks have been used to learn the system dynamics uncertainty bounds by using Lyapunov method. Then the output of these two networks are used to build a sliding mode controller. The stability of the control system is proved and stable neuro-fuzzy controller parameters adjustment laws are selected using Lyapunov theory. Simulation case study shows that the controlled system tracking the reference model effectively with smooth control effort and robust performance has been achieved.