Adaptive Integral Observer-Based Synchronization for Chaotic Systems with Unknown Parameters and Disturbances

Abstract

Considering the effects of external perturbations on the state vector and the output of the original system, this paper proposes a new adaptive integral observer method to deal with chaos synchronization between the drive and response systems with unknown parameters. The analysis and proof are given by means of the Lyapunov stability theorem and Barbalat lemma. This approach has fewer constraints because many parameters related to chaotic system can be unknown, as shown in the paper. Numerical simulations are performed in the end and the results show that the proposed method is not only suitable to the representative chaotic systems but also applied to some neural network chaotic systems.

The Positive Role of Multiplicative Noise in Complete Synchronization of Unidirectionally Coupled Ring with Three Nodes

“…In this example, let = 10, = 24.1, = 8/3. Under this group of parameters, system (20) has chaotic solution.…”

“…The synchronization of nonlinear systems has many potential applications in different areas, such as secure communication [11,12], biological systems [13,14], chemical reactions [15], and physical systems [16]. Due to the potential applications of synchronization, some synchronization methods have been proposed, such as active control [17], adaptive control [18], sliding control [19], and integral observer [20].…”