In this paper, we propose a robust quadratic programming-based control (QPC) for uncertain Euler-Lagrange systems. The key idea of introducing robustness to a QPC is to adopt the disturbance observer (DOB) technique in the QP formulation: that is, an estimate for the lumped disturbance is computed in a least-square sense as the optimal solution of a QP, which is then compensated through the input channel to enhance robustness. Moreover, the input redundancy of the system is additionally utilized for stabilizing null space motion, but with little sacrifice of task space tracking performance. We theoretically prove via the singular perturbation theory that task space dynamics is robustly stable in the presence of model uncertainty, where the concept of the inertially decoupling dynamics is applied. A simulation of a two-link robot manipulator is conducted to verify the effectiveness of the proposed controller.