基于迭代学习观测器的卫星姿态控制系统的鲁棒容错控制

Robust Fault-Tolerant Control for Satellite Attitude Control System Based on Iterative Learning Observer

针对卫星在轨运行时存在执行机构故障和空间干扰问题,提出了一种将迭代学习与未知输入观测器(IL-UIO)相结合的鲁棒容错控制方法。该方法在继承了未知输入观测器干扰解耦优点的同时,运用迭代学习技术,利用前一时刻姿态角速度偏差和IL-UIO输入来更新当前故障信息,实现了执行机构的在线故障重构。进一步基于Lyapunov方法从理论上证明了设计的IL-UIO鲁棒稳定性和姿态角速度偏差一致有界性。最后,建立卫星闭环姿态控制系统对方法进行验证,仿真结果验证了方法的有效性。

Based on Iterative learning-unknown input observer （ IL-UIO ）, a robust fault-tolerant control scheme is pufford to deal with actuator failures and external disturbances of on-orbit satellite. It decouples disturbances with UIO, meanwhile the IL technique are used to update current fault signal by means of immediate past system output errors and the last step IL-UIO information, thus reconstructing actuator fault on-line. Furthermore, the robust stability of the full-order IL-UIO and uniformly boundness of angular velocity errors are proved by using the Lyapunov stability theory. Simulation results of the closed-loop satellite attitude control system used in a satellite attitude control system validate the effectiveness of the proposed method.