Compliance control of a robotic manipulator for ash content detection of flotation tailings

ZHANG Shuxin; WANG Ranfeng; REN Hanchi; ZHANG Linkai; FU Xiang

doi:10.13272/j.issn.1671-251x.2025070069

Abstract：Manual ash content detection of flotation tailings in coal preparation plants has a low degree of automation and cannot meet the requirements of online,rapid,and accurate detection.Applying a robotic manipulator to flotation tailings ash content detection improves detection efficiency and safety.To address the problems of motion stuttering and insufficient compliance of the robotic manipulator during operation,an improved Task-Joint Space Dynamic Adaptive Compliance Control(TJS-DACC)algorithm was proposed.In this algorithm,a reinforcement learning framework was introduced into TJS-DACC,and the response speed and acceleration of the manipulator end effector were comprehensively considered to construct a multi-objective fused reward function.Meanwhile,penalty and loss functions were designed,and an optimization model for the interpolation weight factor"α"was established to achieve adaptive fusion of task-space and joint-space control of the manipulator.Matlab simulation experiments and physical platform experiments were conducted to verify that,when controlled by the improved TJS-DACC algorithm,the sampling efficiency of the flotation tailings ash content detection manipulator increased by 26.13％and 15.03％,respectively,compared with those under the traditional joint-space PID algorithm and the TJS-DACC algorithm.Moreover,the trajectory was continuous and smooth,joint coordination was strong,and no emergency stops,stuttering,or impact phenomena occurred,indicating that the control performance is superior to that of the comparison algorithms.