Adaptive control for a robotic manipulator with uncertainties and input saturations

In this paper, we investigate the control problem of a robotic manipulator with the uncertain dynamics and input saturations. A Model Reference Adaptive Control like (MRAC-like) approach is proposed to solve the problem. The model reference which is Input to State Stable (ISS) and driven by the current designed control is introduced for the filtered velocity tracking error. The uncertain parameters are estimated by using a combination of the regressor and non-regressor based approaches. In the results, the control signal satisfies the input saturations, the semi-global uniform ultimate boundedness of the close loop system is achieved and the tracking error converges to the compact set which depends on the predetermined bound of the control inputs. Simulation results are provided to illustrate the effectiveness of the proposed approach.