Bounding Approach to Fault Detection of Uncertain Dynamic Systems

Abstract

This paper deals with a fault detection method taking model uncertainties into account. Only sensor imperfections are considered; moreover every uncertain parameter is represented by a bounded variable. By this membership approach, a model represents a set of feasible behaviours; therefore, interval analysis is used to build consistency tests based on the parity space approach. A fault is detected when the residual vector is outside its domain of feasible values. Unfortunately, the dependencies between bounded variables make the previous domain too complex to be exactly evaluated. The proposed solution leads to an overestimation obtained by using a paving algorithm.