A Data-Driven Approach to Fault Diagnosis Using Unknown-Input Observers

The core message of this article is to propose a data-driven approach for designing a residual generator based on a dead-beat unknown-input observer (UIO) for linear time-invariant discrete-time state-space models affected by both disturbances and actuator faults. The authors derive necessary and sufficient conditions for the problem solvability using only the available data, without requiring knowledge of the original system matrices.