Synchronization of Nonlinear Chaotic Systems Using Modified Function-Link Fuzzy Cerebellar Model Articulation Controller

This paper presents a modified function-link fuzzy cerebellar model articulation controller for the synchronization of nonlinear chaotic systems including uncertainties, external disturbance, and different initial conditions. This study overlaps the previous state and the current state of Gaussian basis functions on each layer in the cerebellar model articulation controller to make a hybrid of two states. It can adjust the appropriate error values to let the network can efficiently learn parameters, enhance the computational performance and forecast the next state of the inputs. The gradient descent method is used to online adjust the controller parameters, and a Lyapunov stability function is applied to warrant the system’s stability. Simulation studies for the synchronization of the gyroscope and Lorenz chaotic systems manifest that favorable synchronization performance can be attained.

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