Identifying chaotic systems using a fuzzy model coupled with a linear plant

Jiin-Po Yeh

Chaos, Solitons & Fractals, 2007, vol. 32, issue 3, 1178-1187

Abstract: In this paper, a model for identifying chaotic systems is derived from the theory of a feed-forward neural network with three layers. One part of the derived model has the form of a fuzzy logic-based intelligent mechanism; the other part is a linear difference equation, similar to the Wiener-type cascade structure. Three dynamical systems are presented to demonstrate the effectiveness of the proposed model: a one-dimensional logistic map, two-dimensional Hénon map and the continuous-time pendulum system. For both discrete-time and continuous-time chaotic systems, the proposed model always takes the form of a difference equation. Numerical simulations show that the proposed model can well identify the dynamical systems. Time series and time-delayed pseudo-phase plane plots are drawn for both the dynamical systems and the proposed model.

Date: 2007
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:32:y:2007:i:3:p:1178-1187

DOI: 10.1016/j.chaos.2005.11.087

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