Integration of fuzzy logic and chaos theory ebook

Pyragas K Phys. A — CrossRef Google Scholar. Chaos Addison-Wesley Google Scholar. Watts DJ Small Worlds. Evora, Portugal Google Scholar. Short K Int. Zhong Li Xu Zhang There are no affiliations available. Personalised recommendations. Cite chapter How to cite? ENW EndNote. Buy options.

The chapter also describes mathematical methods for controlling chaos in dynamic systems. These methods can be used to control a real dynamic system; however, due to efficiency and accuracy requirements we were forced to use fuzzy logic to model the uncertainty, which is present when numerical simulations are performed. We also describe in this chapter a new theory of chaos using fuzzy logic techniques.

Chaotic behavior in nonlinear dynamical systems is very difficult to detect and control. Part of the problem is that mathematical results for chaos are difficult to use in many cases, and even if one could use them there is an underlying uncertainty in the accuracy of the numerical simulations of the dynamical systems.

For this reason, we can model the uncertainty of detecting the range of values where chaos occurs, using fuzzy set theory. Using fuzzy sets, we can build a theory of fuzzy chaos, where we can use fuzzy sets to describe the behaviors of a system. Unable to display preview. Download preview PDF. Skip to main content. Skip to main content. This service is more advanced with JavaScript available. Advertisement Hide. Self-Reference, Chaos, and Fuzzy Logic.

Authors Authors and affiliations Patrick Grim. This process is experimental and the keywords may be updated as the learning algorithm improves. This is a preview of subscription content, log in to check access. Buckley: Fuzzy dynamical systems I.

In: Proc. Google Scholar. Wang, J. Ou, P. Wang: Dynamic fuzzy sets and fuzzy processes. Bezdek, Seattle, , pp — Google Scholar.

Diamond: Chaos and fuzzy representations of dynamical systems. In: Int. The content of the book covers fuzzy definition of chaos, fuzzy modeling and control of chaotic systems using both Mamdani and Takagi-Sugeno models, fuzzy model identification using genetic algorithms and neural network schemes, bifurcation phenomena and self-referencing in fuzzy systems, complex fuzzy systems and their collective behaviours, as well as some applications of combining fuzzy logic and chaotic dynamics, such as fuzzy-chaos hybrid controllers for nonlinear dynamic systems, and fuzzy-model-based chaotic cryptosystems.

This book can serve as a handy reference for researchers working in interdisciplines related, among others, to both fuzzy logic and chaos theory. Skip to main content Skip to table of contents. Advertisement Hide. This service is more advanced with JavaScript available.

Integration of Fuzzy Logic and Chaos Theory.