This paper proposes an extremum-seeking control approach for the regulation of a class of minimum phase nonlinear systems to the optimum of a measured objective function. The nonlinear systems are subject to the effects of exogenous disturbances driven by unknown dynamics. A Lie bracket averaging technique is used to design the extremum seeking regulation mechanism. The internal model is estimated directly using a derivative action that exploits the convexity of the measured cost function. This mechanism avoids the need for an internal model estimation approach. A stability analysis shows that the system achieves a practical output regulation of the unknown optimum equilibrium. A simulation study demonstrates the effectiveness of the technique.