In this paper, we propose a nonlinear antiwindup scheme to guarantee stability and local performance recovery on Euler-Lagrange systems subject to input magnitude saturation. The antiwindup scheme consists in a dynamic augmentation to the baseline control system which, based on nonlinear analysis, is shown to induce global asymptotic stability and local exponential stability on the overall control scheme. To induce desirable closed-loop performance on a specific system, two parameters of the antiwindup law can be tuned for each position variable of the Euler-Lagrange system, similar to the tuning procedure for proportional-derivative gains. Simulation results are reported showing the behavior of the proposed antiwindup law on the model of a popular industrial robot. The resulting responses confirm the effectiveness of the antiwindup scheme, both for set-point regulation tasks and for trajectory tracking tasks where the saturation nonlinearity is repeatedly activated.