Pusher Reheating Furnace Control: A Fuzzy-Neural Model Predictive Strategy

Icev, Z.A.; Stankovski, Mile; Kolemishevska, T.D.; Zhao, Jun; Dimirovski, Georgi M.

doi:10.3182/20061002-4-bg-4905.00028

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“…In this paper, another alternative control system design with two-layer architecture employing T-S fuzzy predictors [7], which seems rather competitive to the optimization expert [5] based ones. The here proposed Fuzzy Model Predictive Control (FMPC) design is a type of model-predictive control strategy in which the prediction process model is a fuzzy or fuzzy-neural model.…”

Section: Introductionmentioning

confidence: 99%

Pusher reheating furnace control via fuzzy-neural model predictive control synthesis

Stojanovski

Stankovski

Rudas

et al. 2012

2012 6th IEEE INTERNATIONAL CONFERENCE INTELLIGENT SYSTEMS

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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 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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Section: Introductionmentioning

confidence: 99%