UM  > Faculty of Science and Technology  > DEPARTMENT OF ELECTROMECHANICAL ENGINEERING
System modeling and synchronization of nonlinear chaotic systems with uncertainty and disturbance by innovative fuzzy modeling strategy
Li S.-Y.2; Ko L.-W.2; Lin C.-T.2; Tam L.-M.1; Chen H.-K.3; Lao S.-K.1
2013-11-22
Conference NameIEEE International Conference on Fuzzy Systems (FUZZ)
Source Publication2013 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ - IEEE 2013)
Conference DateJUL 07-10, 2013
Conference PlaceHyderabad, INDIA
Abstract

In this paper, an application of the innovative fuzzy model [1] is applied to simulate and synchronize two classical Sprott chaotic systems with unknown noise and disturbance. In traditional Takagi-Sugeno fuzzy (T-S fuzzy) model, there will be 2 linear subsystems (according to 2 fuzzy rules) and m × 2 equations in the T-S fuzzy system, where N is the number of minimum nonlinear terms and m is the order of the system. Through the new fuzzy model, a complicated nonlinear system is linearized to a simple form - linear coupling of only two linear subsystems and the numbers of fuzzy rules can be reduced from 2 to 2 × N. The fuzzy equations become much simpler. There are two Sprott systems in numerical simulations to show the effectiveness and feasibility of new model. © 2013 IEEE.

KeywordFuzz Logic Ge-li Fuzzy Model Linear Matrix Inequality (Lmi)
DOI10.1109/FUZZ-IEEE.2013.6622554
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000335342800256
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Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF ELECTROMECHANICAL ENGINEERING
Affiliation1.Universidade de Macau
2.National Chiao Tung University Taiwan
3.Hsiuping University of Science and Technology
Recommended Citation
GB/T 7714
Li S.-Y.,Ko L.-W.,Lin C.-T.,et al. System modeling and synchronization of nonlinear chaotic systems with uncertainty and disturbance by innovative fuzzy modeling strategy[C],2013.
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