Intermittent fault estimation for satellite attitude control systems based on the unknown input observer

A novel design strategy of an unknown input observer (UIO) based on the radial basis function (RBF) neural network is proposed in this paper for the problem of intermittent fault estimation in the satellite attitude control system subject to the environment disturbance. The unknown input observer is employed to eliminate the interference of the space disturbance. At the meantime, due to the learning ability and nonlinear approximating ability of the radial basis function neural network, the observer is combined with the RBF neural network, so as to estimate the intermittent fault of the satellite attitude control system. Furthermore, a Lyapunov function is used for analyzing the stability of the proposed observer. Finally, the simulation on a closed-loop satellite attitude control system with the environment disturbance demonstrates the high performance of the proposed intermittent fault estimation method both for abrupt and soft faults in the form of additive dynamics.