Titlebook: Integration of Fuzzy Logic and Chaos Theory; Zhong Li,Wolfgang A. Halang,Guanrong Chen Book 2006 Springer-Verlag Berlin Heidelberg 2006 al

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Fuzzy Control of Chaos,the unstable periodic orbits (UPO). Some empirical tricks are introduced for building up a proper fuzzy rule base and designing a fuzzy controller. Finally, an example of fuzzy control of the Chua’s circuit is presented to illustrate the effectiveness of the proposed approach.

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Seminar

Highbrow

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Chaotification of the Fuzzy Hyperbolic Model, control methods to chaotify the FHM and we show that the chaos produced by the present methods satisfy the three criteria of Devaney. We then design a controller based on inverse optimal control and adaptive parameter tuning methods to chaotify the FHM by tracking the dynamics of a chaotic system.

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Fuzzy Chaos Synchronization via Sampled Driving Signals,problem. One of the advantages of the proposed approach is that it allows to express the synchronization problem as a fuzzy logic observer design in terms of linear matrix inequalities, which can be solved numerically using readily advailable software packages. Also, given the linear nature of this

CYT

Bifurcation Phenomena in Elementary Takagi-Sugeno Fuzzy Systems,t simple cases can show a great variety of behaviors. Several local and global bifurcations (some of them, degenerate) are detected and summarized in the corresponding bifurcation diagrams. It is claimed that by carefully making this kind of analysis it is possible to overcome some criticism raised

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Chaotic Behavior in Recurrent Takagi-Sugeno Models, which conditions recurrent rule bases show chaotic behavior in the sense of Li-Yorke?” We determine the minimal number of rules of zero-order and first-order Takagi—Sugeno models with chaotic orbits. We also consider the case of an arbitrary number of rules in such models and high-order time delay

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