Fault diagnosis and fault tolerant control of linear stochastic systems with unknown inputs

This paper presents an integrated robust fault detection and isolation (FDI) and fault tolerant control (FTC) scheme for a fault in actuators or sensors of linear stochastic systems subjected to unknown inputs (disturbances). As usual in this kind of works, it is assumed that single fault occurs at a time and the fault treated is of random bias type. The FDI modules is constructed using banks of robust two-stage Kalman filters, which simultaneously estimate the state and the fault bias, and generate residual sets decoupled from unknown disturbances. All elements of residual sets are evaluated by using a hypothesis statistical test, and the fault is declared according to the prepared decision logic. The FTC module is activated based on the fault indicator, and additive compensation signal is computed using the fault bias estimate and combined to the nominal control law for compensating the fault's effect on the system. Simulation results for the simplified longitudinal flight control system with parameter variations, process and measurement noises demonstrate the effectiveness of the approach proposed.