LAUSR

Abstract In this paper, adaptive control schemes are proposed for the trajectory tracking control of a free-flying space manipulator with guaranteed prescribed performance in the presence of parametric uncertainties, external disturbances, and actuator saturation. Both full-state feedback control and output feedback control are considered. First, a model-based controller is designed by using the barrier Lyapunov function (BLF) to prevent the position tracking errors from exceeding the prescribed performance bounds. Then, a full-state feedback controller is designed by using the radial basis function neural network (RBFNN) to compensate for the lumped uncertainties. Finally, an output feedback controller is designed by using a high-gain observer to estimate the velocity of the space manipulator. Rigorous theoretical analysis for the semi-global uniform ultimate boundedness of the whole closed-loop system is provided. The proposed output feedback controller can guarantee the position and velocity tracking errors converge to the small neighborhoods about zero, while ensuring the position tracking errors within the prescribed performance bounds even without using velocity measurements. To the best of the authors’ knowledge, there are really limited existing controllers can achieve such excellent control performance in the same conditions. Numerical simulations demonstrate the effectiveness and strong robustness of the proposed control schemes.