Robust fault reconstruction method for satellite attitude control system based on iterative learning-unknown input observer

A robust fault reconstruction method based on the iterative learning-unknown input observer (IL-UIO) is proposed for actuator fault in satellite attitude control systems (ACS). Firstly, considering space disturbance torque, model uncertainties and gyro drift, the nonlinear model of attitude control is established when a three-axis stability satellite runs in a small angle maneuver. Secondly, based on the disturbance decoupling principle of UIO and H _∞ control theory, the IL-UIO is designed to estimate attitude Euler angles and angular velocities, and the IL algorithm is used to achieve actuator robust fault reconstruction. Using the Lyapunov stability theorem, the stability of IL-UIO and the ultimate boundedness of dynamic fault errors are proved, the parameter matrixes of IL-UIO are solved effectively in terms of linear matrix inequality (LMI) toolbox. Finally, mathematical simulation is performed to validate the solution in satellite closed-loop ACS, and simulation results demonstrate the effectiveness of the proposed algorithm.