基于集员估计的卫星飞轮故障检测与预测方法

A fault detection and prognosis approach is proposed based on set-membership estimation to achieve early warning of the flywheel fault.Firstly, a zonotope-based fault detection method is designed based on the dynamic model of flywheel.After the flywheel fault is detected, the electric current of flywheel is selected as the fault feature, and the linear model or nonlinear model is used to describe its degradation law.Then, a set-membership algorithm via zonotope is proposed to estimate the unknown parameters of the degradation model.By using the parameter estimation results, fault magnitudes in the future instants are predicted to achieve early warning of the flywheel fault.Finally, the proposed method is compared with two existing fault prognosis techniques through numerical simulation.The simulation results demonstrate the viability and validity of the proposed approach.