APPLICATION OF MODEL REFERENCE ADAPTIVE FUZZY SYSTEM FOR CONTROL OF PROCESS PARAMETERS IN SPONGE IRON PRODUCTION PROCESS

Abstract

Sponge iron is a product of direct reduction of iron ore in a rotary kiln. The reduction process involves a complex chemical reaction which is based on control of temperature and pressure within the kiln. It needs continuous monitoring and control so as to ensure high product quality and also maintain the safety index of the kiln. This is because fluctuations in temperatures and pressure lead to unstable degree of metallization of the product; causing kiln accretion, hot spots and creation of fines that may compromise product quality and shorten the life of the kiln. The formation of accretions in rotary kilns affects the residence time of the charge, kiln hold-up, and the kiln output to a great extent. However accretion build up in the kiln is difficult to regulate during the reduction process for the sponge iron production due to the nonlinear nature of the process dynamics. Thus methods which utilise partial and imprecise data from temperature and pressure sensors to estimate the performance of the kiln need to be implemented to minimize accretion. In this study, a Fuzzy Logic Controller (FLC) that works in conjunction with Model Reference Adaptive Control (MRAC) based on the MIT-Rule is proposed for control of kiln parameters. A MRAC was designed using a PID algorithm technique, and simulation results showed that it can be used in the process parameter control of a rotary kiln thereby minimizing accretion build up in the kiln. MATLAB/SIMULINK was used to simulate the controller models.Simulation results show that it is possible to reduce accretion build up from 27 % when using PID controller to 14.6 % with the use of Fuzzy control. The results of the simulation also indicate that the Model Reference Adaptive Fuzzy System (MRAFS) provides a faster rate of convergence than the conventional MRAC and PID controller approach so that the process tracks the reference model within a shorter time frame. It was also observed that xvii under the same operating conditions, MRAFS has the best dynamic response, shorter response time, low overshoots and high steady precision. The study shows that the developed MRAFS can be used in rotary kilns to maintain product quality as well as minimize accretion formation in the kiln. Key words- Accretion, Fuzzy logic, Kiln, Model Reference Adaptive System, Sponge Iron