Adaptive Backstepping Tracking Control of Wheeled Mobile Manipulator with Output Constraints

Abstract

In this study, an adaptive tracking control scheme with output constraints is proposed for wheeled mobile manipulators. Firstly, a backstepping controller utilizing a time-varying barrier Lyapunov function is proposed to limit the tracking error within prescribed bounds. Further, a radial basis function neural network is employed to compensate for dynamic uncertainties and external disturbances. A stability analysis confirmed the semi-global uniform ultimate boundedness of the controller. Moreover, the results of Matlab simulations demonstrated the improved tracking performance of the proposed system compared with that of the adaptive sliding mode and model-based backstepping controllers. The developed code is publicly available at https://github.com/zhanghuzhenyu/wmm-control .