Open AccessSynchronization of uncertain chaotic systems based on neural network and sliding mode control
Author(s) -
Huaqing Li,
Xiaofeng Liao,
Huang Hong-Yu
Publication year - 2011
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.60.020512
Subject(s) - control theory (sociology) , synchronization (alternating current) , computer science , lorenz system , chen , synchronization of chaos , controller (irrigation) , artificial neural network , chaotic , sliding mode control , mode (computer interface) , function (biology) , interference (communication) , control (management) , nonlinear system , artificial intelligence , physics , computer network , paleontology , channel (broadcasting) , quantum mechanics , evolutionary biology , agronomy , biology , operating system
The synchronization between two unknown chaotic systems is achieved by designing a controller based on the sliding mode control technique and radial basis function neural network. The controller design method is independent of the system mathematical model, but only depends on the output of the system state. Moreover, it is robust to parameter uncertainties and the outside interference. Finally, synchronization between unknown Lorenz systems and between unknown Lorenz system and Chen system are achieved using the proposed method. The response time is very short and the synchronization performance is good.