Synergistic optimization control of blast furnace coal injection based on raceway state feedback

Abstract

Increasing coal and reducing coke is an important technical means to achieve energy conservation and emission reduction. The blast furnace ironmaking process is characterized by large time lag and nonlinearity, and also a lack of information in the manual collaborative operation mode for increasing coal and reducing coke, which leads to the problem that the furnace temperature is difficult to stabilize. The synergistic optimization with a Takagi-Sugeno fuzzy multi-model for a state feedback is proposed. First, the process of increasing coal and reducing coke from the perspective of control is analytically described, converting the stable control problem of molten iron temperature into the tuyere raceway temperature, the state feedback of tuyere raceway temperature and hearth temperature is introduced, based on the establishment of the Takagi-Sugeno fuzzy model of the pulverized coal combustion system in the tuyere raceway, using the principle of parallel distributed compensation algorithm with the help of solving linear matrix inequality, the state feedback controller that satisfies the Lyapunov stability is designed to achieve the temperature stability, thereby ensuring the stability of blast furnace operation under all conditions. Then, the upper and lower synergistic control of increasing coal and reducing coke is realized by the principle of heat balance in high temperature zone and the rule of replacement ratio, to ensure the dynamic balance of temperature in the raceway. Finally, by comparing the simulation results, we found that the proposed method could achieve relatively high stability, meanwhile verify the effectiveness of the coordinated control strategy of reducing coke.