Abstract: Aiming at the problems of low intelligent cutting degree of underground roadheaders, and the swing speed of cutting arms might not be adjusted adaptively according to the hardness of coals and rocks, an adaptive cutting control strategy of roadheader cutting arms was proposed based on multiple sensor information. On the basis of the currents of the cutting motor, the pressures of the driving cylinder of the cutting arms and the vibration accelerations of the cutting arms, the signal recognizer of the cutting loads was designed by using RBF neural network, which provided an accurate basis for the swing speed control of the cutting arms. Aiming at the complex and time-varying swing speed control system of cutting arms, based on genetic algorithm optimization， a fuzzy PID intelligent controller was designed to realize the efficient control of swing speed of cutting arms. The mathematical model of cutting arms of roadheaders was established, and the adaptive cutting simulation control system of cutting arms was built in MATLAB/Simulink. The simulation results show that the control system has fast response speed and high control precision. An airborne adaptive cutting control system of roadheaders was built based on the software of B&R Automation Studio. The simulation cutting experiments were carried out with EBZ135 roadheader in the simulated roadway of Shijiazhuang Coal Mining Machinery Co., Ltd. the experimental results show that the proposed control strategy may realize the efficient adaptive control of the swing speed of cutting arms according to the changes of cutting loads.

Key words: roadheader, radial basis function(RBF) neural network, cutting arm swing speed control, genetic algorithm, fuzzy control

摘要： 针对井下掘进机截割智能化程度低、截割臂摆速不能根据煤岩硬度进行自适应调节的问题，提出了一种基于多传感器信息的掘进机截割臂自适应截割控制策略。以截割电机电流、截割臂驱动油缸压力、截割臂振动加速度作为煤岩截割载荷识别依据，采用径向基函数神经网络设计了截割载荷信号识别器，为截割臂摆速调控提供准确依据；针对复杂且具有时变性的截割臂摆速调控系统，设计了基于遗传算法优化的模糊PID智能控制器，实现对截割臂摆速的高效调控。建立了掘进机截割臂数学模型，在MATLAB/Simulink中搭建了截割臂自适应截割仿真控制系统，仿真结果表明，控制系统具有较快响应速度及较高控制精度。基于贝加莱Automation Studio软件搭建掘进机机载自适应截割控制系统，在石家庄煤矿机械有限公司模拟巷道中采用EBZ135型掘进机进行了模拟截割实验，实验结果表明，所提出的控制策略能够根据截割载荷变化实现对截割臂摆速的高效自适应调控。

关键词: 掘进机, 径向基函数神经网络, 截割臂摆速控制, 遗传算法, 模糊控制