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

Abstract

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.

FWNNet: Presentation of a New Classifier of Brain Tumor Diagnosis Based on Fuzzy Logic and the Wavelet-Based Neural Network Using Machine-Learning Methods

“…The T-S fuzzy models suggested approach for observer-based controller design for uncertain nonlinear systems has been improved [ 24 ]. Zirkohi and Shoja-Majidabad [ 25 ] suggested an efficient adaptive control technique to explore synchronizing two chaotic systems. This method resulted in a type-2 fuzzy wavelet neural network that can better estimate unknown variables and external disturbances in chaotic system dynamics.…”

“…As a model-free controller, this method has many advantages. It was determined that the suggested control approach could ensure the synchronization and stability of the closed-loop control system [ 25 ], employing the Lyapunov stability theory and transient performance analysis.…”

Observer-based adaptive neural network control design for projective synchronization of uncertain chaotic systems

“…An adaptive synchronization method is designed in Heidarzadeh et al (2020) for general chaotic systems subject to unknown dead-zone input nonlinearities. Various adaptive chaos synchronization methods that include universal approximators in their architecture have been also investigated in recent years for either integer-order systems (Boulkroune et al, 2015; Farivar et al, 2012; Izadbakhsh et al, 2021; Zirkohi and Shoja-Majidabad, 2021) or fractional-order systems (Boubellouta and Boulkroune, 2019; Boulkroune and Boubellouta, 2018; Zouari et al, 2017). The principle of approximation-based adaptive chaos synchronization techniques is to use the universal approximators to reconstruct an unknown ideal control signal or to estimate the uncertain nonlinear dynamics.…”

Adaptive nonsingular integral-type dynamic terminal sliding mode synchronizer for disturbed nonlinear systems and its application to secure communication systems

“…Among the most relevant features of chaotic sequences is the close similarity of their behavior to that of noise. This characteristic can be applied to design digital data encryption systems (Nguyen et al, 2020; Moradi Zirkohi and Shoja-Majidabad, 2021; Zarebnia et al, 2019; Zong et al, 2020). Chaotic-based encryption techniques use chaotic sequences and signals made by nonlinear chaotic systems to encrypt systems (Hsiao and Lee, 2015; Liu et al, 2016; Mazloom and Eftekhari-Moghadam, 2009).…”