基于Elman神经网络的采煤机智能调高控制算法研究

Research on Intelligent Height Adjustment Control Algorithm of Shearer Based on Elman Neural Network

为提高采煤机自动调高系统的实时性、跟随性以及稳定性,研究基于Elman神经网络的采煤机智能调高控制算法。通过分析采煤机调高过程,建立采煤机智能调高系统,确定Elman神经网络的输入信号和训练样本,并设计Elman神经网络采煤机智能调高控制算法流程。在仿真环境绘制采煤机滚筒实时位置,基于设计的Elman神经网络算法逼近、拟合采煤机滚筒位置曲线,实时性、跟随性以及稳定性优于BP神经网络算法以及最小二乘算法,提高了采煤机截割滚筒调高控制性能。

In order to improve the real-time,follow-up and stability of the automatic height adjustment system of shearer,the intelligentheight adjustment control algorithm of shearer based on Elman neural network was studied.By analyzing the process of shearer heightadjustment,the intelligent height adjustment system of shearer was established,the input signals and training samples of Elman neural networkwere determined,and the intelligent height adjustment control algorithm flow of shearer based on Elman neural network was designed.Thereal-time position of shearer drum is drawn in the simulation environment.The Elman neural network algorithm based on the designapproximates and fits the position curve of shearer drum.The real-time performance,follow-up performance and stability are better than BPneural network algorithm and least square algorithm,which improves the height adjustment control performance of shearer cutting drum.