SYSTEM-IDENTIFICATION OF A 3-PHASE SUBMERGED-ARC FERROSILICON FURNACE

A 36MW submerged-are ferrosilicon (FeSi) furnace is modeled using the technique of system identification, The main purpose of the modeling i s for the simulation and evaluation of different control schemes, In p articular, the part of the system associated with the control of the t hree-phase electrode currents, which is done by positioning of the ele ctrodes, is examined, Data were collected at Icelandic Alloys Ltd., us ing experiments conducted mostly in open loop, i,e,, data for the dyna mic system identification using electrode positions as inputs and elec trode currents as outputs, as well as data for the estimation of the e ffect of conductance changes, electrode-to-hearth voltages, and other disturbances, using fixed electrode positions and electrode currents a s outputs, The positioning of electrodes responding to control signals was estimated and modeled using measurements in closed loop, It was d ecided to model the process dynamics and the disturbance environment s eparately, since data with inputs varied as well as fixed were readily available and since the disturbances are slowly varying compared to t he process electrode position/current dynamics, Data collection for th e disturbance identification was done by keeping the three electrodes fixed and recording the currents, A first order AR (autoregressive). m odel was used to model the disturbance environment, Data collection fo r the dynamic system identification was done by varying the three elec trode positions and recording the electrode positions and the currents , Different ARX (autoregressive with auxiliary input) MIMO (multiple-i nput/multiple-output) models were tried using several model orders, co mbinations of inputs, and input delays, Then,dependent parameters due to symmetry in the three electrodes, as well as common factors (zeros) in the three input (electrode) polynomials, were eliminated, This was done by using the indirect prediction error method (IPEM) [1], which numerically minimizes a cost function of the difference between the de pendent parameters and the new (independent) ones, Effectively, the re sults obtained in this study indicate that the simple linear models de veloped include all critical factors needed in a simulation of differe nt electrode position based control schemes for the electrode current control of the furnace,