Research on Adaptive Advance Systenn of Hydraulic Support Based on Neural Network PID

被引：0

作者：

Zhou, Guangxin ^{[1
]}

Li, Wei ^{[1
]}

Zhang, Liping ^{[1
]}

机构：

[1] China Univ Min & Technol, CMEE, Xuzhou, Jiangsu, Peoples R China

来源：

ADVANCED MATERIALS AND ENGINEERING MATERIALS, PTS 1 AND 2 | 2012年 / 457-458卷

关键词：

hydraulic support; automatic control; advancing; neural network; PID control;

D O I：

10.4028/www.scientific.net/AMR.457-458.758

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Aiming at the problem that contact advance lags seriously and automatic advance with shearer is not in time in ASQ of hydraulic support on fully mechanized coal mining face, this paper proposed a solution of adaptive advance system based on Neural Network PID. This advance method can effectively reduce invalid waiting time in advance and the probability that friction between top beam and roof increases, and thus to improve advancing velocity and achieve continuity of coal mining automation. This paper finally used SIMULINK to carry out simulation. Results show that Neural Network PID controller has better performance than conventional PID controller.

引用

页码：758 / 763

页数：6