Fast-convergent Fault Detection and Isolation in an Uncertain Scenario

Abstract—In this paper, a fast-convergent fault detection and isolation architecture is proposed for linear MIMO continuoustime systems. By exploiting a system decomposition technique and making use of kernel-based deadbeat estimators, the state variables can be estimated in a non-asymptotic way. Estimation residuals are then defined to detect the occurrence of a fault and identify the occurring fault function after fault detection. In the noisy scenario, thresholds are defined for the residual to distinguish the effect of the noise from that of the fault. Numerical examples are included to characterize the effectiveness of the proposed FDI architecture