Exoskeleton devices are used to assist joint motion of subjects suffering from mobility deficiencies. Controlling an exoskeleton subjects to high nonlinearities, which are mainly due to the mechanical coupling, external disturbances, parameter uncertainties, and modeling errors. Keeping in view the requirement of a relatively accurate movement tracking while reducing the disturbances effects, there is a need for a robust controller. In this paper, an adaptive RISE (Robust Integral of Sign Error) controller is developed and implemented on the EICoSI (Exoskeleton Intelligently Communicating and Sensitive to Intention) knee exoskeleton. RISE has an advantage over standard controllers that it achieves semi-global asymptotic tracking even in the presence of unstructured disturbances. But to achieve this tracking, high control gains are required. Thus, to limit such high gains, RISE control strategy is combined with an adaptive controller, which has the advantage of improving the tracking performance while reducing the eventual overshoots. The stability of the coupled human/ exoskeleton system is analyzed based on Lyapunov theory and the system has shown semi-global asymptotic stability. The adaptive RISE controller gives better SNR (signal to noise ratio) by 11 % and 2 % as compared with adaptive and RISE controller respectively. In terms of tracking error, the adaptive RISE controller shows 9% more error than adaptive controller but 41 % less when compared with RISE controller. Three experimental scenarios are analyzed to validate the proposed controller i.e. (i) external disturbances, that could come from the ground during walking; (ii) induced payload, that could come from the resistive/assistive torque from the muscles and (iii) payload with external disturbances. The system is found to be robust and efficient in tracking the reference trajectories while maintaining limited error and high signal to noise ratio.