| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 721208 | IFAC Proceedings Volumes | 2006 | 6 Pages |
Abstract
A design of fuzzy model-based predictive control for industrial furnaces has been derived and applied to the model of three-zone 25 MW RZS pusher furnace at Skopje Steelworks. The fuzzy-neural variant of Takagi-Sugeno fuzzy model, as an adaptive neuro-fuzzy implementation, is employed as a predictor in a predictive controller. In order to build the predictive controller the adaptation of the fuzzy model using dynamic process information is carried out. Optimization procedure employing a simplified gradient technique is used to calculate predictions of the future control actions.
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Physical Sciences and Engineering
Engineering
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