煤矿工作面需风量预测及通风机智能控制

Prediction and Intelligent Control of Coal Mine Ventilator Air Requirement

为达到对通风机风速控制的准确性和解决传统风速控制方式的问题,在对通风机简单概述的基础上,对工作面需风量的预测展开研究,确定需风量预测的模型;对比了传统PID控制策略、模糊算法控制策略以及T-S模糊神经控制策略的响应特性和超调量,确定采用T-S模糊神经控制策略实现通风机的智能控制,并完成了相关硬件的选型。

In order to achieve the accuracy of ventilator air speed control and solve the problems of traditional air speed control methods,based on a brief overview of the ventilator,the prediction of air demand at the working face is studied to determine the model of air demand prediction;the response characteristics and overshooting amount of traditional PID control strategy,fuzzy algorithmic control strategy and T-S fuzzy neural control strategy are compared to determine the inteligent control of the ventilator by using T-S fuzzy neural control strategy and the selection of related hardware is completed.control strategy to realize the intelligent control of the ventilator,and complete the selection of related hardware.