ON FAILURE DETECTION AND IDENTIFICATION: AN OPTIMUM ROBUST MIN-MAX APPROACH

Abstract

Abstract In this paper, the Failure Detection and Identification (FDI) problem for noise corrupted Linear Time Invariant (LTI) systems is considered. We apply to this problem an optimum min-max robust likelihood ratio testing approach which is known optimal in the Gaussian case. The originality of this approach is that ‘detection probability’ and ‘false alarm probability’ (i.e. power vs. level) in presence of noise are considered when referred to ‘optimality’ and ‘robustness’. Based on this approach, we propose a batch processing algorithm to failure isolation. Then we show that the recursive version reduces to some LQ optimization problem for which we provide a recursive solution. Simulation results on an example related to the lateral motion of a light aircraft are also reported.