关键词: 隧道施工通风, PID控制, 模糊控制, RBF神经网络, 能耗

Abstract:  To ensure construction ventilation quality, control construction ventilation costs, reduce carbon emissions, and improve the applicability of intelligent control model to tunnel construction ventilation systems, a theoretical model based on the CO volume fraction under blasting and mucking conditions is established based on literature research and theoretical analysis methods. In addition, proportionalintegralderivative(PID), fuzzy PID, and radial basis function(RBF) neural networkPID control models are designed for the ventilation systems. Finally, a numerical simulation is performed in MATLAB to compare the parameter determination and control effect of the different control models applied to the proposed theoretical model. The results show that the performance of the control models is negatively correlated with antiinterference to a certain extent. Among the investigated models, PID control model exhibits the best theoretical response because of its convenient parameter determination, whereas fuzzy PID and RBFPID control models best meet the antiinterference and performance requirements of actual projects.

Key words: tunnel construction ventilation, proportionalintegralderivative control, fuzzy control, radial basis function neural network, energy consumption