Study on the Modeling of Main Mine Ventilator Based on Artificial Intelligence

摘要：

The parameters of main ventilator in mine such as air flow, wind speed, gas concentration and other conditions are closely related, for its complexity, its difficult to establish the nonlinear mathematic model, and its hard describe the model properties by traditional identification method. Neural network and Fuzzy system are used in mine main ventilator model identification. A Neural network based on RBF is used in neural network, and a T-S fuzzy model based on triangle membership function is used in Fuzzy identification. The simulation results show that the two methods can satisfy the needs of identification precision, convergence rate, stability and tracking ability simultaneous.

关键词： Ventilaor model System identification RBF-Neural network T-S model

作者: Xinhui Du Shu Niu Xingmin Wang Puhui Wang

作者单位: College of electrical and power engineering, Taiyuan University of Technology, Taiyuan, China College of electrical and power engineering, Taiyuan University of Technology, Taiyuan, China College of electrical and science, Taiyuan University of Technology, Taiyuan, China Electric power of Shanxi, Taiyuan.China

会议类型: 国际会议

会议名称: 2011 3nd International Conference on Mechanical and Electronics Engineering(2011年第三届机械与电子工程国际会议 ICMEE2011)

会议地点: 合肥

会议语种:英文

页码: 3526-3530

在线出版日期: 2011-09-23（万方平台首次上网日期，不代表论文的发表时间）