Application of RBF Hierarchical Neural Network in Automatic Horizon Control System of Memory-cutting Shearer

摘要：

The control of hydraulic servo system is the control key to automatic horizon device of memory-cutting shear. The radial basis function (RBF) hierarchical neural network (RBFHNN) is presented to control the hydraulic servo system of automatic horizon device of memory-cutting shearer. The RBFHNN can identify the sensitivity of the hydraulic servo system in real time in the learning phase, and can make the hydraulic horizon device rapidly track the roof curve of the last cycle as feed-forward controller in the control phase. The simulation results for the hydraulic servo system of shearer horizon device show the control system based on the RBFHNN is faster, and has higher accuracy and better stability.

关键词： Shearer Radial Basis Function, Hierarchical Neural Networks, Automatic Horizon Control

作者: Xiuping Su Wei Li Lili Zhang Yuqiao Wang Qigao Fan Chuantang Sun Ling Yu

作者单位: School of Mechanical and Electrical Engineering, China University of Mining &Technology, Xuzhou, 221 School of Mechanical and Electrical Engineering, China University of Mining &Technology, Xuzhou, 221

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 2015-2018

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）