Predictive Control of Gas Recovery System Based on Neural Network
BIAN He-ying
LI Hong-wei
Abstract：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.
Keywords：steel plantconvertergas recoveryneural networkfuzzy controlpredictive control
Publication Date：2009-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：3( 69-71 )