Pick−and−Place Trajectory Planning and Robust Adaptive Fuzzy Tracking Control for Cable−Based Gangue−Sorting Robots with Model Uncertainties and External Disturbances release_2cjm2xlberdepnpohxyon6kxmu

Abstract

A suspended cable−based parallel robot (CBPR) composed of four cables and an end−grab is employed in a pick−and−place operation of moving target gangues (MTGs) with different shapes, sizes, and masses. This paper focuses on two special problems of pick−and−place trajectory planning and trajectory tracking control of the cable−based gangue−sorting robot in the operation space. First, the kinematic and dynamic models for the cable−based gangue−sorting robots are presented in the presence of model uncertainties and unknown external disturbances. Second, to improve the sorting accuracy and efficiency of sorting system with cable−based gangue−sorting robot, a four-phase pick−and−place trajectory planning scheme based on S-shaped acceleration/deceleration algorithm and quintic polynomial trajectory planning method is proposed, and moreover, a robust adaptive fuzzy tracking control strategy is presented against inevitable uncertainties and unknown external disturbances for trajectory tracking control of the cable−based gangue−sorting robot, where the stability of a closed-loop control scheme is proved with Lyapunov stability theory. Finally, the performances of pick−and−place trajectory planning scheme and robust adaptive tracking control strategy are evaluated through different numerical simulations within Matlab software. The simulation results show smoothness and continuity of pick−and−place trajectory for the end−grab as well as the effectiveness and efficiency to guarantee a stable and accurate pick−and−place trajectory tracking process even in the presence of various uncertainties and external disturbances. The pick−and−place trajectory generation scheme and robust adaptive tracking control strategy proposed in this paper lay the foundation for accurate sorting of MTGs with the robot.
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