Predictive Control of Gas Recovery System Based on Neural Network

In allusion to the problems of low gas recovery rate and big smoke of traditional gas recovery system,the paper put forward a predictive control strategy of gas recovery system based on neural network,which optimizes gas recovery system of a steel plant’s converter by applying neural network adaptive and predictive control and fuzzy control.The simulation results showed that the predictive error of furnace gas emissions was-5～5 L/h and the preditive effect was better.The practice application proved the average recovery of gas reached 97.5 m3/t after applying neural network adaptive and predictive control and it reached the purpose of energy saving,low cost,and protection of environment.