An adaptive fuzzy predictive control of nonlinear processes based on Multi-Kernel least squares support vector regression

In this paper, an adaptive fuzzy Generalized Predictive Control (GPC) is proposed for discrete-time nonlinear systems via Takagi–Sugeno system based Multi-Kernel Least Squares Support Vector Regression (TS-LSSVR). The proposed adaptive TS-LSSVR strategy is constructed using a multi-kernel least squa...

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Bibliographic Details

Published in:	Applied soft computing Vol. 73; pp. 572 - 590
Main Authors:	Boulkaibet, I., Belarbi, K., Bououden, S., Chadli, M., Marwala, T.
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.12.2018
Subjects:	Fixed-budget kernel recursive least-squares Fuzzy c-means clustering Generalized predictive control Least square support vector regression Takagi–Sugeno fuzzy system Takagi–Sugeno fuzzy system Least square support vector regression Fixed-budget kernel recursive least-squares Fuzzy c-means clustering Generalized predictive control
ISSN:	1568-4946, 1872-9681
Online Access:	Get full text
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