Adaptive Neural Network Control of Free-floating Space Manipulator With an Attitude Controlled Base

The control problem of coordinated motion of free-floating space manipulator with an attitude controlled base is
discussed. Firstly, with the Lagrangian formulation and the relationship of the system linear momentum conversation, the dynamic equation of system is derived. Based on the above results and the RBF neural network technique, the Ge-Lee (GL) matrix and its product operator, the dynamics of free-floating space manipulator is approximated. And then with all unknown inertial parameters of the manipulator, the adaptive neural network control scheme of coordinated motion between the base's attitude and the manipulator's joints of free-floating space manipulator is developed. It need neither linearly parameterize the dynamic equation of system, nor know any actual inertial parameters. And the neural network need not do training and learning online too. Therefore, the control scheme is prone to real-time application. Lastly, a planar free-floating space manipulator is simulated to verify the proposed control scheme.