Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
