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

This paper introduces a robust task-space 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 observer-based 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 observer-based robust task-space controller is obtained. In this paper, we proved that the proposed adaptive observer-based controller can guarantee that the task-space 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.