Application of adaptive fuzzy logic systems to model electric arc furnaces

Abstract

Presents the application of adaptive fuzzy logic systems to modelling electric arc furnaces. The main objectives are to provide the rationale and to justify the use of fuzzy modeling for electric furnaces. This is done with reference to three important properties of fuzzy logic systems, namely their nonlinear black-box modeling capability, universal approximation ability and their functional equivalence to radial basis function networks. A detailed investigation regarding the application of adaptive fuzzy logic systems to electric arc furnace modeling is presented. It is demonstrated that the application of adaptive fuzzy logic systems as a nonparametric system identification method to model nonlinear systems can be considered as an alternative to artificial neural networks. The proposed modeling methods are described, and their use is illustrated using actual recorded data.