An adaptive control method to improve the cutting head speed of roadheaders using multisensor information is proposed, so as to solve the problems of low cutting efficiency and low intelligence of roadheaders during underground tunnelling. The operation of a roadheader is analysed, and a control strategy for its cutting head speed is proposed. In addition, the cutting head speed is categorised into five gears according to the multisensor information of different cutting states. The controller for speed estimation is designed using a back propagation neural network optimised using an improved particle swarm optimisation algorithm. A control system is established in MATLAB to analyse the effectiveness of the method. The simulation results show that an IPSO-BP controller has the best control effect and can attain the target speed. The response time was lower than those of fuzzy logic controllers and traditional PI controllers by 46% and 68%, respectively, and the overshoot decreased by 4.69% and 12.19%, respectively. Furthermore, experimental research verified the effectiveness of this method. This method can adaptively adjust the cutting head speed of a roadheader using multisensor information and is important (both theoretical and practically) for extending the service life of roadheaders and improving tunnelling efficiency.

Based on the Lagrange equation in system dynamics, aiming at the horizontal cutting process, the dynamical coupling model of boom‐type roadheader’s body pose was established. According to input problem of solving the model, a calculation method of the cutting head load was proposed, and the relationship between the cutting head load and pressure of the driving cylinders and swing angle of the cutting arm was obtained through simulating analysis. The simulation model was established to solve the dynamical coupling model. The cutting head load, horizontal swing angle of the cutting arm, and dip angle of coal seam were regarded as independent variables to perform changing parameter analysis in variations of the body pose. The field experiment was carried out, and the measured data is basically consistent with the simulation values. The results show that lateral displacement of the body can reach up to 6.5 cm, backward displacement can reach up to 5.2 cm, floor‐based quantity can reach up to 11 cm, pitch angle of the body can reach up to 7.8°, and roll angle can reach up to 2.1°. Variations of the body pose parameters are influenced greatly by the cutting head load, while the influence from horizontal swing angle of the cutting arm and dip angle of coal seam is slighter. Among the pose parameters, floor‐based quantity and pitch angle of the body vary relatively greatly, which tend to seriously influence forming quality of the roadway and should be mainly considered in deviation rectification of the roadheader’s body pose.

A multiparameter control strategy and method for the cutting arm of a roadheader is proposed through the operation analysis of roadheader. The method can address the problems of low intelligence and low cutting efficiency faced by the roadheader in the cutting process. The control strategy is divided into two parts: the cutting load identification part and the swing speed control part. The former part is designed using a backpropagation neural network that is optimized by an improved particle swarm optimization algorithm. The latter part is optimally designed using a fuzzy PID controller with improved simulated annealing particle swarm optimization. The simulation analysis in SIMULINK showed that the response time was reduced, proving the robustness of the method. In addition, experimental studies verified the good control effect of the method under different cutting states. The proposed method uses multiparameter to intelligently change the swing speed, providing a theoretical and practical basis for the realization of intelligent and unmanned cutting of roadheader.

Boom-type roadheader is the most widely used equipment in the fully mechanized excavation face of coal mine. Under complicated operation conditions of underground coal mine, multibody large-scale displacement phenomenon of roadheader will occur during cutting process. Specifically, the position and attitude of the body are changing continuously, and radial runout phenomenon of the cutting arm will take place, which will seriously reduce the overall stability of roadheader and drivage efficiency of the roadway. Focused on the vertical cutting condition, the coupling dynamical model of position and attitude of the body is established based on Lagrange equation. Combined with the calculated cutting load, the dynamical model is solved through Simulink simulation method, and the solving results are analysed under different influence factors. Consequently, the response regularities of position and attitude of the body under influence of different factors are obtained. In the similar way, the dynamical model of radial runout quantity of the cutting arm is established, and the dynamic response of radial runout of the cutting arm during vertical cutting process is obtained as well. Finally, the simulation analysis results are validated through field experiments. The research work of this paper provides useful theoretical basis for deviation rectification control of the multibody structures of roadheader, fills the vacancy of theoretical study in this aspect, and contributes to improving the dynamics theory of mining machinery.

This study presents a dynamical model of the attitude angles of boom-type roadheader, to reveal the response characteristics of the attitude angles in stee