Adaptive impulsive synchronization of uncertain delayed chaotic system with full unknown parameters via discrete-time drive signals

Complexity ◽  
2014 ◽  
Vol 21 (5) ◽  
pp. 43-51 ◽  
Author(s):  
Xiaojing Gao ◽  
Mengfan Cheng ◽  
Hanping Hu
Keyword(s):  
Chaotic System ◽  
Discrete Time ◽  
Unknown Parameters ◽  
Impulsive Synchronization ◽  
Drive Signals

ANTICIPATED FUNCTION SYNCHRONIZATION WITH UNKNOWN PARAMETERS OF DISCRETE-TIME CHAOTIC SYSTEMS

2009 ◽  
Vol 20 (04) ◽  
pp. 597-608 ◽  
Author(s):  
YIN LI ◽  
BIAO LI ◽  
YONG CHEN
Keyword(s):  
Chaotic System ◽  
Discrete Time ◽  
Chaos Synchronization ◽  
Chaotic Systems ◽  
Control Law ◽  
Unknown Parameters ◽  
Synchronization Problem ◽  
Synchronization Scheme ◽  
Hyperchaotic Systems ◽  
Function Synchronization

In this paper, firstly, the control problem for the chaos synchronization of discrete-time chaotic (hyperchaotic) systems with unknown parameters are considered. Next, backstepping control law is derived to make the error signals between drive 2D discrete-time chaotic system and response 2D discrete-time chaotic system with two uncertain parameters asymptotically synchronized. Finally, the approach is extended to the synchronization problem for 3D discrete-time chaotic system with two unknown parameters. Numerical simulations are presented to show the effectiveness of the proposed chaos synchronization scheme.

A new contribution for the impulsive synchronization of fractional-order discrete-time chaotic systems

2017 ◽  
Vol 90 (3) ◽  
pp. 1519-1533 ◽  
Author(s):  
Ouerdia Megherbi ◽  
Hamid Hamiche ◽  
Saïd Djennoune ◽  
Maamar Bettayeb
Keyword(s):  
Fractional Order ◽  
Discrete Time ◽  
Chaotic Systems ◽  
Impulsive Synchronization

scholarly journals Experimental study for impulsive synchronization of a discrete chaotic system

2003 ◽  
Vol 52 (7) ◽  
pp. 1589
Author(s):  
Chen Ju-Fang ◽  
Zhang Ru-Yuan ◽  
Peng Jian-Hua
Keyword(s):  
Experimental Study ◽  
Chaotic System ◽  
Impulsive Synchronization

scholarly journals Parameter Estimation of a Class One-Dimensional Discrete Chaotic System

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Lidong Liu ◽  
Jinfeng Hu ◽  
Huiyong Li ◽  
Jun Li ◽  
Zishu He ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Chaotic System ◽  
Chaos Control ◽  
Mean Value ◽  
Unknown Parameters ◽  
Tent Map ◽  
One Dimensional ◽  
Chebyshev Map ◽  
Mean Value Method ◽  
Control And Synchronization

It is of vital importance to exactly estimate the unknown parameters of chaotic systems in chaos control and synchronization. In this paper, we present a method for estimating one-dimensional discrete chaotic system based on mean value method (MVM). It is proposed by exploiting the ergodic and synchronization features of chaos. It can effectively estimate the parameter value, and it is more exact than MVM. Finally, numerical simulations on Chebyshev map and Tent map show that the proposed method has better performance of parameter estimation than MVM.

Model-free adaptive PID control for nonlinear discrete-time systems

2020 ◽  
Vol 42 (10) ◽  
pp. 1797-1807 ◽  
Author(s):  
Shuhua Zhang ◽  
Ronghu Chi
Keyword(s):  
Discrete Time ◽  
Mathematical Analysis ◽  
Pid Control ◽  
Contraction Mapping Principle ◽  
Unknown Parameters ◽  
Model Free ◽  
Discrete Time Systems ◽  
Gradient Parameter ◽  
Adaptive Pid Control ◽  
Time Systems

This work explores a model-free adaptive PID (MFA-PID) control for nonlinear discrete-time systems with rigorous mathematical analysis under a data-driven framework. An improved compact form dynamic linearization (iCFDL) is proposed to transfer the original nonlinear system into an affined linear data model including a nonlinear residual term. Both a time-difference estimator and a gradient parameter estimator are designed to estimate the nonlinear residual uncertainties and the unknown parameters in the iCFDL model. Subsequently, a novel improved CFDL based MFA-PID (iCFDL-MFA-PID) control is proposed by incorporating these two estimators. The results are extended by the use of improved partial format dynamic linearization (iPFDL) and full format dynamic linearization (iFFDL). The theoretical results are shown using contraction mapping principle-based mathematical analysis, as well as simulations.

LAG PROJECTIVE STOCHASTIC PERTURBED SYNCHRONIZATION FOR CHAOTIC SYSTEMS AND ITS APPLICATION IN SECURE COMMUNICATION

2008 ◽  
Vol 22 (24) ◽  
pp. 4175-4188 ◽  
Author(s):  
YANG TANG ◽  
JIAN-AN FANG ◽  
LIANG CHEN
Keyword(s):  
Chaotic System ◽  
Secure Communication ◽  
Chaotic Systems ◽  
Stochastic Perturbation ◽  
Projective Synchronization ◽  
Unknown Parameters ◽  
Adaptive Feedback ◽  
Communication Scheme ◽  
Simulation Results ◽  
Feedback Method

In this paper, a simple and systematic adaptive feedback method for achieving lag projective stochastic perturbed synchronization of a new four-wing chaotic system with unknown parameters is presented. Moreover, a secure communication scheme based on the adaptive feedback lag projective synchronization of the new chaotic systems with stochastic perturbation and unknown parameters is presented. The simulation results show the feasibility of the proposed method.

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