Intelligence control for friction compensation in precision pointing and tracking system

In order to compensate for the influence of friction in the coarse pointing subsystem of the precision pointing and tracking system, an adaptive RBF terminal sliding mode control was proposed, and CA (Genetic Algorithm) was applied off line to parameter identification of the friction model. A terminal sliding mode controller was used to obtain a stable and fast trajectory first, then the upper bound of friction was estimated through an adaptive RBF neural network. The system was proved to be stable and the parameters are proved to be bounded under the control scheme of this paper, using Lyapunov methodology. At last, simulation results show the highly robust and efficient controller design.