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Automatic T-S fuzzy model with application to designing predictive controller
Computer Science and Information Systems, Tome 9 (2012) no. 4 Cet article a éte moissonné depuis la source Computer Science and Information Systems website

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A novel methodology is proposed to automatically extract T-S fuzzy model with enhanced performance using VABC-FCM algorithm, a novel Variable string length Artificial Bee Colony algorithm (VABC) based Fuzzy C-Mean clustering technique. Such automatic methodology not requires a priori specification of the rule number and has low approximation error and high prediction accuracy with appreciate rule number. Afterward, a new predictive controller is then proposed by using the automatic T-S fuzzy model as the dynamic predictive model and VABC as the rolling optimizer. Some experiments were conducted on the superheated steam temperature in power plant to validate the performance of the proposed predictive controller. It suggests that the proposed controller has powerful performance and outperforms some other popular controllers.
Keywords: T-S fuzzy model, fuzzy c-means; automatic; Artificial Bee Colony; predictive control, superheated steam temperature 
@article{CSIS_2012_9_4_a11,
     author = {Zhi-gang Su and Pei-hong Wang and Yu-fei Zhang},
     title = {Automatic {T-S} fuzzy model with application to designing predictive controller},
     journal = {Computer Science and Information Systems},
     year = {2012},
     volume = {9},
     number = {4},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2012_9_4_a11/}
}
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AU  - Pei-hong Wang
AU  - Yu-fei Zhang
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Zhi-gang Su; Pei-hong Wang; Yu-fei Zhang. Automatic T-S fuzzy model with application to designing predictive controller. Computer Science and Information Systems, Tome 9 (2012) no. 4. http://geodesic.mathdoc.fr/item/CSIS_2012_9_4_a11/