航天器姿控系统的PD型学习观测器故障重构

针对满足Lipschitz条件的航天器姿态控制系统这一非线性系统中存在的执行器加性故障、空间干扰与测量噪声问题,提出了基于PD型迭代学习观测器的故障重构方法。该方法具有期望的鲁棒性能指标,能够在系统存在空间干扰与测量噪声情况下实现对突变故障与时变故障等故障类型的精确重构。基于线性矩阵不等式技术给出系统化PD型迭代学习观测器的设计方法,并根据Lyapunov稳定性理论对上述设计方法的稳定性条件进行了理论证明,同时利用鲁棒技术抑制空间干扰与测量噪声对执行器故障重构的影响,通过线性矩阵不等式工具箱求解观测器参数矩阵。最后,将该方法应用到航天器姿态控制系统中,仿真结果证明了该方法的有效性。

PD-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.