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 experi-ments were carried out under two different body poses of the roadheaders.The experimental results il-lustrate that the maximum contour errors are within 48 mm and 52 mm(about 2.14％and 2.32％)re-spectively,which verifies the effectiveness of the proposed self-positioning cutting control method for the roadheaders.
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