Supervision of nonlinear adaptive controllers based on fuzzy models

A novel approach for the supervision of fuzzy model on-line adaptation is proposed. A nonlinear predictive controller is designed based on a Takagi–Sugeno fuzzy model. By adapting the fuzzy model on-line, high control performance can be achieved even with time-variant process behaviour and changing...

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Bibliographic Details

Published in:	Control engineering practice Vol. 8; no. 10; pp. 1093 - 1105
Main Authors:	Fink, Alexander, Fischer, Martin, Nelles, Oliver, Isermann, Rolf
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.10.2000
Subjects:	Adaptive control Heat exchanger Nonlinear control On-line adaptation Recursive least squares (RLS) Takagi–Sugeno fuzzy models Variable forgetting factor On-line adaptation Recursive least squares (RLS) Takagi–Sugeno fuzzy models Heat exchanger Variable forgetting factor Adaptive control Nonlinear control
ISSN:	0967-0661, 1873-6939
Online Access:	Get full text
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