Trajectory Tracking Control Method of Shaft Arm of Coal Mine Boring Machinery Based on Improved Variable Gain Iterative Learning Algorithm
Traditional control methods are often difficult to achieve the ideal control effect in the trajectory tracking of the mechanical axle arm of coal mine robots.To address this problem,an innovative control method is proposed,which is based on an iterative learning algorithm and incorporates the variable gain technique to improve the control and tracking performance of the robotic system on the trajectory path of the mechanical axis arm.By analyzing the joint space trajectory planning and Cartesian space trajectory planning,the demand of the trajectory tracking control of the mechanical arm is clarified,and the variable gain iterative learning algorithm is introduced to improve the robustness of the algorithm.The results show that under different load conditions,the time consumption of the proposed method is at the minimum value,and the variable joint angle and direction angle tracking curves of the robotic arm are small in actual operation.The above results show that the proposed method has a very superior tracking control effect on the trajectory planning of the robotic arm of the roadheader.
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