On the Adaptive Performance Control of Robot Manipulators

In this paper, we propose an adaptive performance control (APC) framework for output-feedback control of robot manipulators with input constraints, focusing on achieving joint position tracking with adaptive performance attributes. Building on the APC methodology, we introduce a single-funnel control approach that dynamically adjusts performance constraints to accommodate the actuator limitations inherent in robotic systems. Moreover, a robust tracking differentiator with predefined convergence characteristics is developed to estimate the unmeasured velocity errors. The effectiveness of the proposed control scheme is validated through simulation results on a 2-DoF planar manipulator and experiments on a 3-fingered 12 degree-of-freedom robotic hand tasked with performing a musical piece on a keyboard.