基于BP神经网络的采煤机自动调高PID控制系统研究

Research on Automatic Lifting PID Control System of Shearer Based on BP Neural Network

由于采煤机记忆截割技术应用在复杂煤层中具有局限性,提出一种基于BP神经网络的PID控制器,对采煤机的液压自动调高系统进行优化。通过BP神经网络的预测控制原理,改进PID控制器参数。搭建了采煤机滚筒调高PID控制实验系统,并进行了阶跃响应实验和跟踪性能实验。结果表明,相比于传统PID控制器,改进的PID控制器响应更为平稳、跟踪性能更加优越,能更好地满足采煤机在复杂工况下的自动调高要求。

Due to the application limitation of memory cutting technology for shearer in complex coal seam,a PID controller based on BP neural network was proposed to optimize the hydraulic automatic lifting system of shearer.The prediction control principle of BP neural network was used to improve PID controller parameters.The PID control experiment system of shearer drum height adjustment was built,and the step response test and tracking performance test were carried out.The results show that the improved PID controller has more stable response and better tracking performance,and can better meet the requirements of automatic control of shearer in complex working conditions,compared with the traditional PID controller.