Chaos synchronization using an improved type-2 fuzzy wavelet neural network with application to secure communication

In this article, a simple yet efficient adaptive control method is proposed to investigate synchronizing two chaotic systems. This approach presents an improved type-2 fuzzy wavelet neural network for estimating the unknown terms and the external disturbance in the chaotic systems' dynamics. Furthermore, an efficient robust control term is integrated into the suggested controller so that the robustness of the controller against system unknown disturbances and uncertainties is improved. This approach offers a very desirable characteristic as a model-free controller. With the help of the Lyapunov stability theory supported with the transient performance analysis, it is established that the proposed control scheme can guarantee the synchronization and the stability of the closed-loop control system. Comparative simulation results with radial basis function neural networks are given that prove the proposed method has superiority in secure communication applications.

Automated summary

This article presents an improved type-2 fuzzy wavelet neural network for synchronizing chaotic systems, with an integrated robust control term to enhance controller effectiveness. The proposed control scheme guarantees synchronization and stability of the closed-loop control system through Lyapunov stability theory. Comparative simulation results demonstrate its superiority in secure communication applications over radial basis function neural networks.