| The reheating furnace is not only one of most important equipment of the steel mill, but also a large energy consumer on steel rolling line, and its consumption occupies about 25 percent of the energy consumption of the steel industry. Reheating furnace control technology directly affects the quality of rolled steel products energy consumption and mill life. Executing the optimal control of the reheating furnace is significant for iron and steel.The purpose of reheat furnace production is to acquire the slab temperature distribution rolling required, and achieve the fewest stock scale loss, energy consumption and environment pollution. Because the furnace combustion process is affected by random disturbances more and it's of nonlinearity, great inertia and coupling, so it is difficult to establish an accurate mode of controlled object, and achieve the ideal result by traditional control methods, which depend on the experience of the personnel operator to control the set values of lower level control loop. When the boundary conations change, which usually makes the technical specification actual values deviate the scope of target, and result decline in product quality, energy consumption increases. Quantitative feedback theory is a fashionable robust control theory rapidly developed in recent years, which has the advantage of engineering practicability, which don not need to know the precise mathematical model of controlled object. For the above, the quantitative feedback theory and fuzzy control technology are applied to reheating furnace control, and make research on these key problems including, temperature control, combustion control and optimizing ration of air to fuel. Specifically, this paper includes the main work as follows: First of all, this thesis has a profound research on combustion mechanism of reheating furnace, and using temperature combustion cascade control methods to control temperature automatically. Proposing establish furnace temperature model by experimental models, the least square method on the model parameters identification. According to the identification, a temperature controller is designed temperature design based on QFT. Meanwhile, using fuzzy control technology to improve the controller's performance, and achieve online parameters self-tuning to improve the adaptability of the system. Second, we improve double cross limiting model slow response problems. After analyzing the relationship between combustion efficiency and air-fuel ratio, according to the problem of the best air/fuel excurses with fuel calorific value and changes in furnace conditions, optimization of air/fuel ratio's fuzzy controller assorting with the feed forward of the calorimeter based on temperature change and oxygen content of furnace flue. Combustion efficiency got improved. Finally, the control system simulation and performance analysis show that designed controller is robust on the furnace operating conditions change, system performance become well both in response and economy.Based on the deep analysis of the reheating furnace characteristic, the reheating furnace temperature combustion control system has been designed, especially the optimizing design of Air/Fuel ratio and the improving of double-cross limit control model has great reference value both in academic research and practical applications in engineering. |
