Self-positioning Cutting Control Methods and Experimental Research for Coal Mine Roadheaders

A self-positioning cutting control methods were proposed, and the experimental studies of roadheaders were conducted herein. An self-positioning cutting control strategy was proposed. The monocular vision and deep learning based six degrees of freedom pose detection method for roadheader body and the double-layer fuzzy adaptive backstepping control method with prescribed performance were utilized to achieve the self-positioning cutting of roadheaders. The tracking control of cutting head was realized at arbitrary body poses of the roadheaders. The cutting head tracking control experiments were carried out under two different body poses of the roadheaders. The experimental results illustrate that the maximum contour errors arc within 48 mm and 52 mmCabout 2.14% and 2.32%) respectively, which verifies the effectiveness of the proposed self-positioning cutting control method for the roadheaders. © 2024 Chinese Mechanical Engineering Society. All rights reserved.