@article {10.3844/jcssp.2011.197.205,
article_type = {journal},
title = {Synchronization of Chaos Systems Using Fuzzy Logic},
author = {Ababneh, Mohammad and Etier, Issa and Smadi, Mahmoud and Ghaeb, Jasim},
volume = {7},
number = {2},
year = {2011},
month = {Feb},
pages = {197-205},
doi = {10.3844/jcssp.2011.197.205},
url = {https://thescipub.com/abstract/jcssp.2011.197.205},
abstract = {Problem statement: This study presented a new and systematic method to robustly
synchronize uncertain chaos systems. It was derived based on the observer approach for
synchronization, where error dynamics was made asymptotically stable around the zero to accomplish
synchronization. Approach: This method viewed the synchronization problem as a control problem in
order to make use of the literature available in this field. In addition, it consisted of designing a digital
response system to synchronize with a given continuous-time chaotic drive system. Takagi-Sugeno
(TS) fuzzy model was used to model the chaotic dynamic system, while the uncertainties were
decomposed such that the uncertain chaotic system could be rewritten as a set of local linear models
with an additional disturbed input. Results: This study demonstrated the effectiveness of the
methodology presented. The response (receiver) system was able to synchronize very closely with
drive (transmitter) system. Furthermore, both piecewise linear and nonlinear uncertain Chua circuits
synchronized wonderfully with insignificant errors. Conclusion: The study confirmed that it is capable
of achieving excellent synchronization performances, even in the presence of significant parametric
uncertainties for uncertain chaos systems. The Takagi-Sugeno (TS) fuzzy model was used to model the
chaotic dynamic system, while the uncertainties are decomposed such that the uncertain chaotic system
was rewritten as a set of local linear models with an additional disturbed input.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}