An adaptive nonsingular terminal sliding mode tracking control using neural networks for space manipulators actuated by CMGs

An adaptive non-singular terminal sliding mode (ANTSM) trajectory tracking control scheme based on neural networks is proposed for rigid space manipulators with control moment gyroscopes (CMGs) as reactionless actuators. A key feature of this scheme is that an adaptive neural network is used to learn the upper bound of the system lumped uncertainties with no prior knowledge. A nonsingular terminal sliding surface is constructed to ensure that the tracking error converges to zero in finite time on the sliding surface. An adaptive law is also proposed for the control gain’s adjustment. The closed-loop system is uniformly ultimately bounded proved by Lyapunov’s method. Simulation results verify the effectiveness of the proposed controller and the robustness of the space manipulators.