Designing a Robust Control Scheme for Robotic Systems with an Adaptive Observer

This paper introduces a robust taskspace control scheme for a robotic system with an adaptive observer. The proposed approach does not require the availability of the system states and an adaptive observer is developed to estimate the state variables. These estimated states are then used in the control scheme. First, the dynamic model of a robot is derived. Next, an observerbased robust control scheme is designed to compensate the uncertainties occurring in the control system. Moreover, upper bound of the lumped uncertainty is essential in the design of the robust controller. However, the upper bound of the lumped uncertainty is difficult to obtain in practical applications. Therefore, an adaptive law is derived to adapt the value of the lumped uncertainty, and an adaptive observerbased robust taskspace controller is obtained. In this paper, we proved that the proposed adaptive observerbased controller can guarantee that the taskspace tracking error and also the observation error converge to zero. To demonstrate the effectiveness of the proposed method, simulation results are illustrated in this paper.