Finite-time trajectory tracking control of space manipulator under actuator saturation

This paper studies the finite-time trajectory tracking control of a space manipulator under model uncertainty, external disturbance and actuator saturation. The dynamics of space manipulator is derived using Kane's method. Considering the model uncertainty that may exist when the manipulator captures an unknown payload, a radial basis function (RBF) neural network (NN) is used to estimate the uncertain model of the space manipulator. An auxiliary system is designed to compensate the actuator saturation. Then a NN-based adaptive terminal sliding mode controller is proposed for trajectory tracking of a space manipulator. The stability of the proposed controller is analyzed using Lyapunov theory. Numerical simulations are conducted to verify the effectiveness of the proposed controller.