TY - JOUR
T1 - Exponential synchronization of two totally different chaotic systems based on a unified model
AU - Liu, Meiqin
AU - Chen, Haiyang
AU - Zhang, Senlin
AU - Fan, Zhen
N1 - Publisher Copyright:
© 2014, The Natural Computing Applications Forum.
PY - 2014/12
Y1 - 2014/12
N2 - This paper presents an exponential synchronization scheme between two chaotic systems with different structures and parameters. A unified model consisting of a linear dynamic system and a bounded static nonlinear operator is employed to describe these totally different chaotic systems. A novel state feedback control law is established to exponentially synchronize the two unified models with different parameters. Most chaotic systems with different structures and parameters, such as Hopfield neural networks, cellular neural networks, Chua’s circuits, unified chaotic systems, Qi systems, and chaotic recurrent multilayer perceptrons, can be transformed into this unified model with the synchronization controller designed in a unified way. Two numerical examples are exploited to illustrate the effectiveness of the proposed design schemes.
AB - This paper presents an exponential synchronization scheme between two chaotic systems with different structures and parameters. A unified model consisting of a linear dynamic system and a bounded static nonlinear operator is employed to describe these totally different chaotic systems. A novel state feedback control law is established to exponentially synchronize the two unified models with different parameters. Most chaotic systems with different structures and parameters, such as Hopfield neural networks, cellular neural networks, Chua’s circuits, unified chaotic systems, Qi systems, and chaotic recurrent multilayer perceptrons, can be transformed into this unified model with the synchronization controller designed in a unified way. Two numerical examples are exploited to illustrate the effectiveness of the proposed design schemes.
KW - Different chaotic systems
KW - Exponential synchronization
KW - Time delays
KW - Unified model
UR - https://www.scopus.com/pages/publications/84920258787
U2 - 10.1007/s00521-014-1670-5
DO - 10.1007/s00521-014-1670-5
M3 - 文章
AN - SCOPUS:84920258787
SN - 0941-0643
VL - 25
SP - 1801
EP - 1808
JO - Neural Computing and Applications
JF - Neural Computing and Applications
IS - 7-8
ER -