Adaptive Tracking Control of Space Continuum Robots based on a State Observer

Abstract

For space continuum robot with limited observation, an adaptive tracking control scheme based on a state observer is proposed in this paper. Firstly, an observer based on saturation functions is adopted to estimate the robot's angular velocity. Then, a global information vector is constructed and approximated online by a radial basis function (RBF) neural network. Finally, an adaptive controller with the global information vector is designed. The controller has high tracking accuracy and strong robustness in terms of the model errors and external disturbances. The asymptotic stability of the robot system is verified via the Lyapunov theory. Simulation results show that the designed controller can effectively deal with model errors and external disturbances of the space continuum robot and improve the tracking accuracy.