Tuning Function-Based Prescribed Performance Control of Robotic Manipulators With Discontinuous References

This paper deals with the issue of reference tracking for the robotic manipulators with piecewise continuous references. Discontinuities in the reference signals lead to abrupt changes in both the tracking errors and intermediate errors, thereby posing significant challenges to existing prescribed performance control (PPC) design approaches. To tackle this challenge, a scheme based on tuning functions for adjusting the performance envelope is introduced. In this manner, the performance functions are suitably adjusted to address the discontinuous errors, guaranteeing that timely convergence to the predefined bounds following the reference jumps. In addition, this scheme is compatible with standard PPC methods because it retains the natural robustness of PPC against system model uncertainties. In spite of the existence of unknown nonlinearities, the utilization of fuzzy logic systems or neural networks for approximation has become unnecessary. The theoretical findings are experimentally validated through simulations performed on a 2-DoF robotic manipulator.