Prescribed Performance Control for Uncertain Euler-Lagrange Systems with Constrained Inputs via Virtual-Only Reference Modification

In this paper, we propose a novel prescribed performance control (PPC) scheme for uncertain Euler-Lagrange systems subject to input constraints. Traditional PPC methods often struggle with input limitations, requiring potentially unbounded control efforts to meet performance specifications. To address this challenge, we introduce a reference modification mechanism that adjusts only the virtual reference signal for the velocity whenever the control input saturates. This approach ensures that the position tracking errors remain within predefined prescribed performance bounds, achieving precise tracking without steady-state error despite input constraints. We derive lower bounds for the input saturation levels that guarantee the feasibility of the control scheme and prove that all closed-loop signals remain bounded. Simulation results on a BlueRov2 underwater vehicle model demonstrate the effectiveness of the proposed method.