Dynamic reconstruction of nonlinear v-i characteristic in electric arc furnaces using adaptive neuro-fuzzy rule-based networks

作者：Sadeghian A^*; Lavers J D

来源：Applied Soft Computing, 2011, 11(1): 1448-1456.

DOI：10.1016/j.asoc.2010.04.016

• Electric arc furnaces
• Modeling
• Fuzzy rule-base
• Adaptive neuro-fuzzy network

This paper presents an application of adaptive neuro-fuzzy networks which dynamically reconstructs the model of nonlinear v-i characteristic in electric arc furnaces. Electric arc furnaces represent complex, multi-variable processes with time-variant parameters, and their effective modeling is a challenging task. This paper shows that adaptive neuro-fuzzy networks lend themselves well to nonlinear black-box modeling of v-i behavior of electric arc furnaces. A successful implementation is described, and its performance is illustrated in comparison to measurements from an operational furnace.

• 出版日期2011-1