On-line evolution of Takagi-Sugeno fuzzy models
Angelov, Plamen and Victor, Jose and Dourado, Antonio and Filev, Dimitar
(2004)
On-line evolution of Takagi-Sugeno fuzzy models.
In: 2nd IFAC Workshop on Advanced Fuzzy/Neural Control, 2004-09-16 - 2004-09-17.
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Abstract
Evolving Takagi-Sugeno (eTS) fuzzy models and the method for their on-line identification has been recently introduced for both MISO and MIMO case. In this paper, the mechanism for rule-base evolution, one of the central points of the algorithm together with the recursive clustering and modified recursive least squares (RLS) estimation, is studied in detail. Different scenarios are considered for the rule base upgrade and modification. The radius of influence of each fuzzy rule is considered to be a vector instead of a scalar as in the original eTS approach, allowing different areas of the data space to be covered by each input variable. Simulation results using a well-known benchmark (Mackey-Glass chaotic time-series prediction) are presented. Copyright © 2004 IFAC
Item Type:
Contribution to Conference
(Paper)
Journal or Publication Title:
2nd IFAC Workshop on Advanced Fuzzy/Neural Control
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Uncontrolled Keywords:
/dk/atira/pure/researchoutput/libraryofcongress/qa75
Subjects:
?? evolving takagi-sugeno fuzzy modelsrule-base evolutionrecursive clusteringrls algorithm. dcs-publications-idinproc-338dcs-publications-creditsdsp-fadcs-publications-personnel-id82qa75 electronic computers. computer science ??
Deposited On:
11 Jan 2008 11:25
Last Modified:
19 Sep 2024 01:19