D-type learning observer based fault reconstruction for spacecraft attitude control systems

A fault reconstruction method based on PD-type iterative learning observer is proposed to deal with actuator additive faults, space external disturbances and measurement noises existing in the nonlinear systems such as spacecraft attitude control systems, which satisfy Lipschitz conditions. The method has the desired robust performance index, and can achieve accurate reconstruction of abrupt faults, time-varying faults, etc. in the presence of space external disturbances and measurement noises. The designed method of PD-type iterative learning observer is given based on linear matrix inequality technique, and the stability condition of the method is proved according to the Lyapunov stability theory. The influence of space external disturbances and measurement noises on actuator additive faults reconstruction is suppressed using robust technology and also linear matrix inequality toolkit solving observer parameter matrix. The method is applied to spacecraft attitude control system. Simulation results show the effectiveness of the proposed method.