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Under the condition of a short sampling period, limited resource and computational capacity, a method for designing reduced-order fault detection filtering algorithm is proposed in this paper. Small perturbation theory and a Taylor series expansion about the balance point are used to linearize the nonlinear dynamics equations of space vehicles. Then the reduced-order fault detection filter is designed for the linear state-space equation. The problem of feasible solution of the reduced-order fault detection filtering algorithm is transformed into a nonconvex optimization problem expressed in terms of linear matrix inequalities. The local optimal solution of the nonconvex optimization is achieved by an alternate mapping algorithm. The reduced-order fault detection filtering algorithm is obtained under the condition that the feasible solution exists. Finally, the reduced-order fault detection algorithm is applied to the fault detection of the yaw control system in a small-scale autonomous helicopter. Simulation results are presented to show effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The problem of robust fault detection is studied for a class of networked control system for flight vehicles with Markov short delay and packet dropout. The networked control system for flight vehicle is modeled as a discrete finite Markov jump linear system by combining Markov short delay and packet dropout as a finite Markov process and establishing corresponding model for packet dropout. Based on this model, the residual generator is constructed and the problem of fault detection is formulated as a H∞ filtering problem. The existence condition of the fault detection filter and the solutions are derived by using the linear matrix inequality technique. Simulation results show that the modeling method can reduce the influence of packet dropout on fault detection capability effectively. The results also show that the proposed fault detection method is sensitive to the fault and robust to unknown disturbance. [ABSTRACT FROM AUTHOR]

An actuator fault diagnosis approach is proposed for linear systems and a class of nonlinear systems with Lipschitz constraints. Considering the actuator fault as an auxiliary state vector, an augmented system is constructed. And then an augmented state observer is designed by the linear matrix inequality technique. The asymptotic estimates of the original system state vector and the actuator fault term are obtained simultaneously. Stability and convergence of the proposed observer is analyzed based on the Lyapunov theory. Finally, the proposed approach is applied to actuator fault diagnosis for the satellite attitude control system. Simulation examples illustrate the effectiveness of the presented method. [ABSTRACT FROM AUTHOR]

An anti-saturation guidance law designed by finite-time theory is proposed in this paper, which can solve the problem that system states may be saturated in the guidance process. The sufficient conditions are proposed by means of Differential Linear Matrix Inequalities to guarantee the system both Input-Output Finite-time Stabilization and Finite-Time Boundedness. Then the anti-saturation guidance law design method is presented. While ensuring that the system state is bounded, the method uses a pre-given finite-time interval and pre-given weighted matrix functions to characterize the requirements for the system dynamic characteristics. The simulation results also show that the proposed method can drive the line of sight angular rate near zero in the finite-time interval, while the acceleration does not exceed the physical limitations. [ABSTRACT FROM AUTHOR]