摘要
针对现有多级胶带调速系统采用二维模糊控制算法存在调节速度与期望速度误差较大的问题,建立了自适应神经模糊推理系统模型,设计了一种基于自适应神经模糊推理系统模型的多级胶带调速系统。该调速系统以第1条胶带的瞬时流量和实时速度为输入量,以变频器的调节频率为输出量实现调速。Matlab仿真结果表明,引入自适应神经模糊推理系统模型的多级胶带调速系统的速度误差可控制在2%以下,运量与带速匹配率得到了优化,对现今煤矿企业的节能减排具有一定的应用价值。
In view of problem of big error between adjustment speed and expected speed of existing multistage belt speed-regualtion system adopting two-dimensional fuzzy control algorithm,a kind of adaptive neural fuzzy inference system（ANFIS）model was established,and a multistage belt speedregualtion system based on ANFIS was designed.The speed-regualtion system takes instantaneous flow and real-time speed of the first belt as input,and takes regulating frequency of frequency converter as output to realize speed control.The Matlab simulation results show that the speed control error of the speed-regualtion system introducing ANFIS model is below 2%,capacity and belt speed matching rate are optimized,which has certain application value for energy saving and emission reduction of coal mine enterprises.
出处
《工矿自动化》
北大核心
2017年第1期42-47,共6页
Journal Of Mine Automation
