Robust adaptive control scheme for optical tracking telescopes with unknown disturbances

In this paper, a robust adaptive control scheme is proposed for optical tracking telescopes with parametric uncertainty, unknown external disturbance and input saturation. To improve tracking performance of this robust adaptive control scheme, a nonlinear disturbance observer (NDO) is employed to tackle the integrated effect amalgamated from unknown parameters, unknown external disturbance and input saturation. At the same time, the radial basis function neural network (RBFNN) is introduced to approximate the input of an unknown function. Utilizing the estimated outputs of NDO and RBFNN, the robust adaptive control scheme is developed for optical tracking telescopes. Stability of the closed-loop system is rigourously proved via Lyapunov analysis and the convergent tracking error is guaranteed for optical tracking telescopes. Numerical simulation results are presented to illustrate the effectiveness of the proposed robust adaptive control scheme based on RBFNN and NDO for the uncertain dynamic of optical tracking telescopes.