Research on Trajectory Tracking Control of Non-Singular Fast Terminal Sliding Mode Iterative Learning for Robot Manipulators

In response to the challcngc of precise trajectory tracking control for robot manipulators, influenced by the aecuraey of modcling parameters and disturbance uncertaintics, a novel control approach that combines non-singular fast terminal sliding mode control with iterative learning control is presented. First, to ensurc the convergence speed of tracking errors and prevent singularity issues during convergence, a non-singular fast terminal sliding mode Controller employing the law of approach to Saturation is designed. Second, to further improve trajectory tracking aecuraey, an error iterative learning Controller is developed, and the convergence of these Controllers is analyzed. Finally, the control System based on the proposed method is implemented in Simulink for iterative and comparative control Simulation experiments. Additionally, real-machinc experiments for robot manipulator tracking control are carried out. The experimental results show that: in the iterative experiment, the maximum average steady-statc error in joints inercases by 72%; in the comparative experiment, comparcd to PD-type iterative learning control and PD-typc linear sliding mode control, the maximum average steady-state error rises by 97% and 51%, respectively, while the maximum response adjustment time decreases by 70% and 50%, respectively; in the real-machine experiment, the robot manipulator tracking error stabilizes within the ränge of [—0. 05, 0. 05] rad. These findings thoroughly validate the effectiveness and aecuraey of the proposed control method, offering an effective control Solution for addressing uncertainties in robot manipulator trajeetory tracking. © 2025 Xi'an Jiaotong University. All rights reserved.