基于迭代学习观测器的卫星姿态滑模容错控制

为解决卫星上反作用飞轮存在安装偏差、故障及外部干扰情况下的姿态控制问题,提出了一种基于迭代学习观测器的姿态容错控制方法。该方法通过设计迭代学习观测器,以较小的计算量实现对执行机构发生的故障以及安装偏差进行精确的估计。并利用观测器的观测结果设计滑模控制器,使处于外部干扰条件下的卫星系统在执行机构发生故障的情况下可以快速稳定地完成姿态机动任务。进一步基于Lyapunov稳定性定理证明了迭代学习观测器及控制器的全局渐近稳定性。针对反作用飞轮存在不确定性及故障的情况下进行仿真,仿真结果表明,与同类容错控制方法相比,所提方法可以更加快速精确地对故障进行估计并完成姿态控制。

Sliding Mode Fault Tolerant Attitude Control for Satellite Based on Iterative Learning Observer

In order to solve the attitude control problem for satellite with unknown reaction wheel faults, uncertainties and unknown external disturbances, a novel fault tolerant attitude control scheme is proposed based on Iterative learning observer (ILO). More specially, an Iterative learning observer is derived to estimate reaction wheel faults and uncertainties accurately with less on-line computing power. Secondly, a sliding mode controller is derived based on the estimated information, to achieve the attitude stability of satellite rapidly with unknown external disturbances and reaction wheel faults. Furthermore, the stability of the Iterative learning observer (ILO) and the globally asymptotically stability of the controller are approved by using the Lyapunov stability theory. Finally, simulations are carried out for satellite with unknown reaction wheel faults, uncertainties and disturbances, the results demonstrate that the proposed control scheme is more effectively and feasibility by comparing with other fault tolerant control approach.