In a general direct adaptive robust control (DARC) framework, the emphasis is always on the guaranteed transient performance and accurate trajectory tracking in presence of uncertain nonlinearities and parametric uncertainties. Such a direct algorithm suffers from lack of modularity, controller-estimator inseparability, and poor convergence of parameter estimates. In the DARC design the parameters are estimated by gradient law with the sole purpose of reducing tracking error, which is typical of a Lyapunov-type design. However, when the controller-estimator module is expected to assist in secondary purposes such as health monitoring and fault detection, the requirement of having accurate online parameter estimates is as important as the need for the smaller tracking error. In this paper, we consider the trajectory tracking of a robotic manipulator driven by electro-hydraulic actuators. The controller is constructed based on the indirect adaptive robust control (IARC) framework with necessary design modifications required to accommodate uncertain and nonsmooth nonlinearities of the hydraulic system. The online parameter estimates are obtained through a parameter adaptation algorithm that is based on physical plant dynamics rather than the tracking error dynamics. While the new controller preserves the nice properties of the DARC design such as prescribed output tracking transient performance and final tracking accuracy, more accurate parameter estimates are obtained for prognosis and diagnosis purpose. Comparative experimental results are presented to show the effectiveness of the proposed algorithm.