TY - JOUR
T1 - Synchronization of chaotic systems from a fuzzy regulation approach
AU - Meda-Campaña, J. A.
AU - Castillo-Toledo, B.
AU - Chen, G.
N1 - Funding Information:
Work partially supported by Consejo Nacional de Ciencia y Tecnología (CONACYT) through research project 46538-A and scholarship SNI; and by Instituto Politécnico Nacional (IPN) through research project 20080445 and scholarships COFAA and EDI. ∗Corresponding author. Tel.: +525557296000. E-mail addresses: jesus_meda@yahoo.com, jmedac@ipn.mx (J.A. Meda-Campaña).
PY - 2009/10/1
Y1 - 2009/10/1
N2 - In this paper, some results on fuzzy regulation and fuzzy modeling are presented for synchronization of chaotic systems described by Takagi-Sugeno (TS) fuzzy models using linear local controllers. It is shown that the synchronization error is bounded if the local controller can be appropriately designed, and that such an error is independent of initial conditions. This feature allows synchronizing not only similar chaotic systems but, under certain conditions, different chaotic systems can be synchronized as well. In other words, this approach can be used to obtain either complete or generalized synchronization. Several simulations are carried out to illustrate how the problem can be solved in a practical way by using the linear matrix inequalities (LMI) technique.
AB - In this paper, some results on fuzzy regulation and fuzzy modeling are presented for synchronization of chaotic systems described by Takagi-Sugeno (TS) fuzzy models using linear local controllers. It is shown that the synchronization error is bounded if the local controller can be appropriately designed, and that such an error is independent of initial conditions. This feature allows synchronizing not only similar chaotic systems but, under certain conditions, different chaotic systems can be synchronized as well. In other words, this approach can be used to obtain either complete or generalized synchronization. Several simulations are carried out to illustrate how the problem can be solved in a practical way by using the linear matrix inequalities (LMI) technique.
KW - Chaos synchronization
KW - Regulation theory
KW - Takagi-Sugeno fuzzy model
UR - http://www.scopus.com/inward/record.url?scp=68149179723&partnerID=8YFLogxK
U2 - 10.1016/j.fss.2008.12.006
DO - 10.1016/j.fss.2008.12.006
M3 - Artículo
SN - 0165-0114
VL - 160
SP - 2860
EP - 2875
JO - Fuzzy Sets and Systems
JF - Fuzzy Sets and Systems
IS - 19
ER -