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In this work, a novel self-organizing interval type-2 fuzzy cerebellar model articulation controller design for chaotic systems synchronization is presented. A function-link network and an asymmetric-membership function are employed to improve the learning ability and flexibility of the proposed network. The gradient-descent method is used to derive the adaptive laws for online updating the network parameters. Suitable learning rates for adaptive laws can be achieved by employing the modified Jaya algorithm. Furthermore, the proposed self-organizing algorithm is used to generate new fuzzy rules or delete less-active fuzzy rules. The control system's exponential stability is analyzed by applying the Lyapunov theory. Finally, numerical simulations on the synchronization of four-dimensional chaotic systems (considering external disturbances and system uncertainties) are conducted to validate the efficiency and performance of the proposed method.

Optimum Design of Function-Link Type-2 Fuzzy Asymmetric CMAC Based on Self-Organizing Algorithm and Modified Jaya Algorithm