  We study in this paper the problem of adaptive trajectory tracking for
nonlinear systems affine in the control with bounded state-dependent and
time-dependent uncertainties. We propose to use a modular approach, in the
sense that we first design a robust nonlinear state feedback which renders the
closed loop input to state stable(ISS) between an estimation error of the
uncertain parameters and an output tracking error. Next, we complement this
robust ISS controller with a model-free multiparametric extremum seeking (MES)
algorithm to estimate the model uncertainties. The combination of the ISS
feedback and the MES algorithm gives an indirect adaptive controller. We show
the efficiency of this approach on a two-link robot manipulator example.
