Application of Optimal Control Strategy to Converter Gas Recovery System
转炉煤气回收系统优化控制策略应用

The characteristics of converter gas recovery process and the important factor in the effect of recycling are analyzed, run indicators of process parameters to achieve optimal control of the recycling process are described, and an optimal control strategy to increase CO concentration is raised. Fuzzy radical basis function (RBF) neural network is used to online identify the mathematical model between pressure of converter mouth and the CO concentration. The identified model is used to optimize pressure settings and control the pressure of converter mouth near the set value, thus significantly increasing the effect of CO concentration. Network learning algorithm is improved in the process of identification, so that the network is robust and easy to convergence for the variational learning parameters. The application of the optimal control strategy in a gas recovery system shows that this optimal control strategy can significantly improve the quality and quality of gas recovery, and achieve good application results.