Study on neural network adaptive control method for uncertain space manipulator

An adaptive control method based on neural network for the model uncertainty of free float space manipulator is proposed. A RBF neural network is used to approximate the nonlinear model of the space manipulator and learn the upper bound of the dynamic uncertainty. The neural network UUB problem is solved by the adaptive law, and path planning of free float space manipulator in Cartesian space is completed. The adaptive law for the weights of RBF neural network is presented which can ensure the stability of the space manipulator system. Simulations illustrate that the method avoids parameter linearization of the space manipulator dynamic model and decreases the computation, satisfy the actual mission of real-time as well.