Robust trajectory tracking of a 3D-printed rapid prototyping manipulator through variable gain super-twisting algorithm - Sujian Wu; Jinyuan Hu; Guohua Shi; Jinyu Fan; Yunyao Li (Measurement + Control, 2025)
This paper deals with the design of a variable gain super-twisting algorithm-based controller to solve the high tracking performance, low identification cost, and parameter tuning problem for rapid prototyping manipulators. The key elements of the proposed controller approach are the inverse dynamics-based controller, tracking differentiator (TD), and the variable gain super-twisting algorithm (VGSTA) controller. The inverse dynamic controller relies on part of the dynamic model information, which reduces the identification cost and decouples the manipulator’s torque input. The motion for using VGSTA, apart from its property of providing robustness to the system with respect to the unmodeled part and uncertainties, is also given by its capability of enforcing the controlled objects to the sliding surface in finite time and more explicit tuning parameter, allowing one to tune the system dynamic performance more simply. The proposal has been verified in a 3D-printed rapid prototyping manipulator, the experiment includes the parameter tuning experiment and the controller dynamic performance experiment. The manipulator’s dynamic performance and robustness are identified on the basis of the above experiment.