Turkish Journal of Electrical Engineering and Computer Sciences
DOI
-
Abstract
In this paper, two mathematical ways of building a fuzzy model of both linear and nonlinear systems are presented and compared. In order to determine a model for a nonlinear system, the phase plane is divided into sub-regions and a linear model is assigned for each of these regions. This linear model is represented either in state-space or ARX model form. To determine the pre-selected parameters of the linear system model under study, least-square identification method is used. Then these linear models are arranged in a fuzzy manner to characterize the overall system behavior. The results show that this method can identify linear systems exactly and nonlinear ones quite satisfactorily with both system representations, assuming that the input-output data is not corrupted by noise.
First Page
125
Last Page
135
Recommended Citation
EKSİN, İBRAHİM and EROL, OSMAN KAAN (2000) "A Fuzzy Identification Method for Nonlinear Systems," Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 8: No. 2, Article 4. Available at: https://journals.tubitak.gov.tr/elektrik/vol8/iss2/4
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