Intelligent Sinter Machine Speed Control System Using Optimized Fuzzy Logic Controller: An Experimental Study in Iron and Steel Plant

Abstract

Intelligent control systems developed for production facilities significantly contribute to production efficiency and quality. Using intelligent control systems has now become a necessity in iron and steel sintering plants that produce millions of tonnes annually. Automatic control of the sinter machine speed, which directly affects production efficiency and quality, is one of the first issues to be addressed. The complexity of the sintering process, being affected by many variables, and the nonlinearity of these variables make it difficult to control the machine speed. This study demonstrates that we have overcome this challenge using a fuzzy logic controller (FLC), which is optimized with an adaptive neuro-fuzzy inference system (ANFIS). The FLC we have designed operates with the characteristic point of the thermal state, the mixture level, the vacuum average, and the current speed parameters. We achieved an average success rate of 95%. The developed system automatically controls the speed of the sinter machine with high accuracy, independent of the operator. The system we have developed is used continuously at the Iskenderun Iron & Steel Co. sinter plant. The results obtained from the production facility show that the developed system captures the thermal change in the sinter pallet and manages the machine accordingly, increases the sintering efficiency by at least 10%, and ensures process safety. These results revealed that the developed system can be used effectively in the iron and steel industry and the use of the system will increase efficiency.