Intelligent roadheader lateral optimization control method and system

Abstract

The invention discloses a lateral optimization control method and system for an intelligent roadheader. The boundary line of the left and right roadway walls is generated by laser radar, and a lateral optimal controller is designed based on the boundary line. It does not rely on positioning and map information, and effectively solves the problem of underground positioning. , The problem of difficult map construction; based on the kinematic model of the roadheader and the boundary line constraints of the left and right road walls, trajectory clusters under different articulation angular velocities are generated, and the control evaluation function is designed to select the optimal motion trajectory and calculate the optimal expected articulation angle to ensure that the system Satisfy the demand for high-precision control; according to the average error, maximum error, and terminal error of the trajectory relative to the center line, the lane wall collision is graded and early-warned, which reduces the driving difficulty of the driver (safety officer) in the mine and improves the safety of the roadheader's underground operation.

Description

technical field [0001] The invention relates to the field of roadheader tracking control, in particular to an intelligent roadheader lateral optimization control method and system. Background technique [0002] Tracking control of roadheader is one of the important contents of unmanned mine research. It is a key technology for unmanned underground operation of roadheader. It has important application value for improving the intelligent level of mine equipment and realizing "green mine". To realize the tracking control of the roadheader, it is necessary to overcome the particularity of the underground environment and meet the high-precision control requirements, especially to avoid the collision between the roadheader and the roadway wall. In practical application, there are still the following problems to be solved: [0003] (1) The underground environment is dark, and it is difficult to drive the roadheader, and it is difficult for the driver (safety officer) to judge whet...

AI Technical Summary

Problems solved by technology

[0003] (1) The underground environment is dark, and the roadheader is difficult to drive, and it is difficult for the driver (safety officer) to judge whether there is a risk of collision during driving

At present, most of the research on roadheader collision avoidance focuses on collision avoidance devices or passive safety, and there is no public lateral control method that considers roadheader and underground roadway wall collision avoidance;

[0004] (2) The underground roadway is narrow, and the lateral control error is generally required to be no more than 30cm. It is difficult for the traditional geometric control algorithm to meet the high-precision control requirements. Modern optimal control methods (such as LQR, MPC, etc.) have large calculation loads, poor real-time performance, and May not have a feasible solution, etc.

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