Control strategy for an intelligent shearer height adjusting system

查看全文 作　　者：FAN Qigao, LI Wei, WANG Yuqiao, ZHOU Lijuan, YANG Xuefeng, YE Guo School of Mechanical & Electrical Engineering, China University of Mining & Technology, Xuzhou 221008, China

出　　处：《Mining Science and Technology》索引2010年第20卷第6期,共5页

基　　金：support for this work, provided by the National High Technology Research and Development Program of China (No2008AA062202);China University of Mining & Technology Scaling Program 摘　　要：An intelligent shearer height adjusting system is a key technology for mining at a man-less working face. A control strategy for a shearer height adjusting system based on a mathematical model of the height adjusting mechanism is proposed. It considers the non-linearity and time variations in the control process and uses Dynamic Fuzzy Neural Networks (D-FNN). The inverse characteristics of the system are studied. An adaptive on-line learning and error compensation mechanism guarantees sys-tem real-time performance and reliability. Parameters from a German Eickhoff SL500 shearer were used with Matlab/Simulink to simulate a height adjusting control system. Simulation shows that the trace error of a D-FNN controller is smaller than that of a PID controller. Also, the D-FNN control scheme has good generalization and tracking performance, which allow it to satisfy the needs of a shearer height adjusting system. 关键词：调节系统控制策略采煤机动态模糊神经网络智能模糊神经网络控制器 SIMULINK PID控制器

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Control strategy for an intelligent shearer height adjusting system

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