Adaptive synchronization between two different chaotic systems with unknown parameters

By Huaguang Zhang, Zhiliang Wang, Tianyou Chai. 2006

229 citations recorded by the source corpus.

A unified mathematical expression describing a class of chaotic systems is presented, for which the problem of adaptive synchronization between two different chaotic systems with unknown parameters has been studied. Based on Lyapunov stability theory, an adaptive synchronization controller is designed and analytic expression of the controller and the adaptive laws of parameters are developed. The adaptive synchronizations between Lorenz and Chen systems, a modified Chua's circuit and Rossler systems are taken as two illustrative examples to show the effectiveness of the proposed method.

Subfields: Computer Networks and Communications, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/d0ee10203836c09f9a58d5a82896d84f3ea4c635

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Tiedong Ma
2. Zhiliang Wang
3. G. Huang
4. Peng Shi
5. H. Su
6. Jian Chu
7. Zhengguang Wu
8. Ning Sun

In Statistical and Nonlinear Physics

1. Tiedong Ma
2. Zhiliang Wang
3. M. Mossa Al-sawalha
4. Peng Shi
5. H. Su
6. Jian Chu
7. Zhengguang Wu
8. G. Huang

Citations in the corpus

• Adaptive anti-synchronization of two identical and different hyperchaotic systems with uncertain parameters (2010, background): “A wide variety of approaches have been proposed for the synchronization or anti-synchronization of hyperchaotic systems, that include generalized active control [5–10], nonlinear control [11,12], adaptive control [13–21].”
• Stochastic Synchronization of Markovian Jump Neural Networks With Time-Varying Delay Using Sampled Data (2013, background): “In the past years, a lot of results have been proposed for the synchronization of chaotic systems [12], [14], [23], [33].”
• Robust Global Exponential Synchronization of Uncertain Chaotic Delayed Neural Networks via Dual-Stage Impulsive Control (2010, methodology): “Generally speaking, to achieve the synchronization between different chaotic systems or identical ones with different parametric uncertainties, complicated continuous controllers are often required to compensate for the structure mismatch [ 13 ], [14], [27], [28], [51].”
• Stability analysis for nonlinear fractional-order systems based on comparison principle (2014, background): “Due to many potential applications, controlling and synchronizing chaotic systems have drawn a lot of researchers’ attention in recent years [20–23].”