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On Fuzzy Control of Chaotic Systems

On fuzzy control of chaotic systems
Authors: Issam A. Smadi; Ahmad Harb;

On Fuzzy Control of Chaotic Systems

Abstract

In this paper, we introduce the control of the strange attractor, chaos. Because of the importance of controlling undesirable behavior in systems. researchers are investigating the use of linear and nonlinear controllers, either to remove such oscillations (in power systems) or to match two chaotic systems (in secure communications). The idea of using the fuzzy logic concept for controlling chaotic behavior is presented. There are two good reasons for using fulzy control: first, there is no mathematical model available for the process; secondly. it can satisfy nonlinear control that can be developed empirically. without complicated mathematics. The two systems are well-known models so the first reason is not a big problem. and we can take advantage of the second reason.

Keywords

Fuzzy control/observation systems, chaos, nonlinear theory, fuzzy control, Strange attractors, chaotic dynamics of systems with hyperbolic behavior

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    citations
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    17
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Top 10%
Average
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