Steel Sintering Waste Heat Recovery Process Steam Temperature Intelligent Control Method Study

Sintering waste heat recovery process is a very complicated industrial process, which can be interfered by many factors. The interference come from sintering progress and the feature of nonlinearity, large inertia in waste heat recovery progress are the major control challenges. The main problem of optimizing control is how to set appropriate operating parameters so as to bring more energy from sintering sensible heat and to increase the stability of the system.This paper introduces the index of boiler' s effective heat production, to evaluate the overall efficiency of waste heat power generation system, and proposes an operating parameters optimization method based on this index. First, the BP neural network is applied to predict the index, so that the optimization model for boiler' s effective heat production is constructed. Based on this model, an improved particle swarm optimization is developed, in order to obtain the optimal values of middle-pressure steam's temperature and cool-machine speed, which result in the maximal boiler' s effective heat production.On the basis of the optimization set value, a predictive-feedback fuzzy controller is designed to control the temperature of middle-pressure steam. Sinter characterization temperature is imported into temperature control system as feed forward parameters to establish the middle-pressure steam temperature prediction model. The prediction fuzzy controller uses the steam temperature' s deviation of predicted and set value as input, the feedback fuzzy controller use the deviation of actual and set value as input, an integrated controller combined with prediction fuzzy and feedback fuzzy controller is designed to realize the stable control of middle-pressure steam temperature.The industrial operation data is applied to the simulation and experimental research on steam temperature optimization control. The stimulation shows that, the particle swarm algorithm can be used to develop middle-pressure boiler' s effective production optimization model, and can increase the efficiency of waste heat recovery system. Compared with the pure feedback fuzzy controller, the middle-pressure steam temperature predict-feedback intelligent control strategy has smaller overshoot and shorter respond time. This paper provides new idea for optimization control in sintering waste heat recovery process, which can improve the waste heat recovery system's efficiency and stability.