Adaptive Modified Function Projective Lag Synchronization for Two Different Chaotic Systems with Stochastic Unknown Parameters

2015 ◽  
Vol 13 (3) ◽  
pp. 1391-1405 ◽  
Author(s):  
Zengyun Wang ◽  
Lihong Huang ◽  
Xuxin Yang
Keyword(s):  
Chaotic Systems ◽  
Unknown Parameters ◽  
Lag Synchronization ◽  
Projective Lag Synchronization ◽  
Different Chaotic Systems

Chaos Synchronization in a Class of Chaotic Systems Using Kalman Filter and Feedback Linearization Methods

2006 ◽  
Author(s):  
Hassan Salarieh ◽  
Aria Alasty
Keyword(s):  
Kalman Filter ◽  
Feedback Linearization ◽  
High Performance ◽  
Chaotic Systems ◽  
Chaotic Behavior ◽  
Drive System ◽  
Unknown Parameters ◽  
Linearization Methods ◽  
Filter Approach ◽  
Different Chaotic Systems

In this paper a combination of Kalman filter and feedback linearization methods is used to present a controller-identifier system for synchronizing two different chaotic systems. The drive system has some unknown parameters which are supposed to have linear form within its dynamic equation. An identifier based on Kalman filter approach is designed to estimate the unknown parameters of the drive system, and simultaneously a feedback linearizing controller is used to synchronize the chaotic behavior of the response system with the drive chaotic system. The method proposed in this paper is applied to the Lure’ and the Genesio dynamic systems as the drive and response chaotic systems. The results show the high performance of the method to identify and synchronize two different chaotic systems with unknown parameters and in presence of noise.

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