In this paper,a new nonlinear augmented observer is proposed and applied to satellite attitude control systems.The observer can estimate system state and actuator fault simultaneously.It can enhance the performances of rapidly-varying faults estimation.Only original system matrices are adopted in the parameter design.The considered faults can be unbounded,and the proposed augmented observer can estimate a large class of faults.Systems without disturbances and the fault whose finite times derivatives are zero piecewise are initially considered,followed by a discussion of a general situation where the system is subject to disturbances and the finite times derivatives of the faults are not null but bounded.For the considered nonlinear system,convergence conditions of the observer are provided and the stability analysis is performed using Lyapunov direct method.Then a feasible algorithm is explored to compute the observer parameters using linear matrix inequalities(LMIs).Finally,the effectiveness of the proposed approach is illustrated by considering an example of a closed-loop satellite attitude control system.The simulation results show satisfactory performance in estimating states and actuator faults.It also shows that multiple faults can be estimated successfully.
This paper aims at rescheduling of observing spacecraft imaging plans under uncertainties. Firstly, uncertainties in spacecraft observation scheduling are analyzed. Then, considering the uncertainties with fuzzy features, this paper proposes a fuzzy neural network and a hybrid rescheduling policy to deal with them. It then establishes a mathematical model and manages to solve the rescheduling problem by proposing an ant colony algorithm, which introduces an adaptive control mechanism and takes advantage of the information in an existing schedule. Finally, the above method is applied to solve the rescheduling problem of a certain type of earth-observing satellite.The computation of the example shows that the approach is feasible and effective in dealing with uncertainties in spacecraft observation scheduling. The approach designed here can be useful in solving the problem that the original schedule is contaminated by disturbances.
