Abstract: Trajectory tracking control problems of freefloating space manipulators with uncertainty are considered, and a robust adaptive control method is put forward based on neural network. The dynamics model of uncertain space manipulators is established, and the unknown nonlinear parts of system model are considered. A neural network controller is designed to approach the unknown uncertain parts, by the way the traditional upper bound of conservative is be avoided estimating. Taylor technology is used to linearize the Gaussian function of neural network hidden layer. Then the adaptive learning laws of the network weight parameters, the hidden layer center and width of Gaussian function are designed to guarantee the online realtime adjustment. The robust adaptive controller is designed to compensate the amount of highorder item and the approximation errors for better control accuracy. The uniformly ultimately bounded (UUB) of the closedloop system is proved based on the Lyapunov theory. Simulation results show that the proposed control method can get better control accuracy, and the controller has important engineering value for the space manipulator.

Key words: space manipulator； neural network, robust control, adaptive control； uniformly ultimately bounded