摘要
针对煤矿局部通风机传统调速系统存在的实时性低、稳定性差、调速算法落后的问题,设计基于T-S模糊神经网络控制的局部通风机智能调速系统。在分析、对比PID调速、模糊调速方案的优缺点的基础上,确定基于T-S模糊神经网络控制调速算法。根据T-S模糊控制原理、结构、学习过程设计局部通风机智能调速方案设计以及仿真模型搭建。仿真结果表明,设计并实现的基于T-S模糊神经网络控制的局部通风机智能调速方案实时性强、跟随性好、稳定性高,调速效果明显。
Aiming at the problems of low real-time performance,poor stability,and backward speed control algorithm in the traditional speed control system of coal mine partial ventilator,an intelligent speed control system for partial ventilator based on T-S fuzzy neural network control is designed.On the basis of analyzing and comparing the advantages and disadvantages of PID speed control and fuzzy speed control scheme,the speed control algorithm based on T-S fuzzy neural network is determined.According to the T-S fuzzy control principle,structure and learning process,the intelligent speed regulation scheme design and simulation model construction of partial ventilator are designed.The simulation results show that the designed and implemented intelligent speed regulation scheme of partial ventilator based on T-S fuzzy neural network control has strong real-time performance,good followability,high stability and obvious speed regulation effect.
作者
曹建文
CAO Jianwen(CCTEG Taiyuan Research Institute Co.,Ltd.,Taiyuan030006China;National Engimeering Laboratory for Coal Mining Machinery,Taiyuan030006China)
出处
《煤矿现代化》
2022年第1期64-67,共4页
Coal Mine Modernization
关键词
T-S模糊控制
PID控制
智能调速
仿真
局部通风机
T-S fuzzy control
PID control
intelligent speed regulation
simulation
partial ventilator