08-01-2014, 04:25 PM
Comparative study of BOF Steelmaking Process based on ANFIS and GRNN Model
Abstract
BOF steelmaking process is most important process to obtain the desired quality of steel consideration of two parameter end point temperature and end point carbon percentage by two model ANFIS and GRNN. The main aim of present paper is steelmaking through Basic Oxygen Furnace (BOF) to achieve higher productivity and the lower production cost in the minimum time by desired endpoint carbon content and temperature of raw material (molten steel). It is a very complicated physical chemical process however most of the industries use it. To achieve this various modeling are used such as mechanistic model, statistical model, regression and neural network models.
Neural Network usages Fuzzy Logic Controllers is adaptive in nature and gives superior and faster results, without using of accurate mathematical model and well response for complex non-linear multi dimensional system. The present paper about controlling the end point of carbon content and temperature in basic oxygen furnace process using ANFIS and GRNN model and compression the both results. ANFIS has provided a new method for solving the problem of prediction and control of end point carbon content and end point temperature of complex BOF process. ANFIS model have five layers but GRNN have only two that’s the main reason behind the more accuracy of ANFIS model.