| Energy and environmental issues of today become the focus of the world, with iron ore prices increased year by year and the advent of low-carbon economy, as the steel industry to be in the highly competitive international market to survive, we must reduce energy consumption per unit of product, reduce environmental pollution. Thus reducing production costs and enhancing their overall competitiveness in order to open prospects for the development of enterprises.This paper analyzes the days of Tianjin iron and steel group2#existing combustion control, mainly taken the master-slave cascade PID control, the main gas flow and the air-fuel ratio is manually set, different individuals operating practices coupled with furnace conditions of instability and other factors, the control effect is not entirely satisfactory, could be improved. In comparing the existing hot air furnace control system advantages and disadvantages of each control method, the characteristics of combustion system for the stove, the fuzzy control, neural networks, and the two can be combined with introduction of the done analysis, and fuzzy control technology and combination of neural networks, a method based on fuzzy neural network control for burning stove. Through control of fuzzy control the experience of skilled workers, as well as mass production through the analysis of data obtained by application of fuzzy control rules in the study, application of BP neural network implementation of fuzzy control rules. Meet the demand of the control of combustion stove by fuzzy neural network.The MATLAB software for the simulation experiment results show that the control unit can fully meet the control requirements stove and reduce the energy consumption of the product, thereby reducing the labor intensity, creating a build-effectiveness for the enterprise. |
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