Faster and more accurate FDI for hybrid systems using hybrid possible conflicts

Abstract

Model-based fault isolation and identification in hybrid systems is computationally expensive or even unfeasible for complex systems due to the presence of uncertainty concerning the actual state, and also due to the presence of both discrete and parametric faults coupled with changing modes in the system. In this work we improve fault isolation and identification performance for hybrid systems diagnosis using Hybrid Possible Conflicts. Fault detection with Hybrid Possible Conflicts relied upon a statistical test to decide when a significant deviation in the residual occurs. Fault detection time is later used to trigger the fault isolation and identification stages. In this work we propose to analyze the evolution of the residual signal using CUSUM to find a more accurate estimation of the time of fault occurrence, which allows to improve both the potential new modes tracking and the parametric fault identification. Moreover, we extend our previous proposal for fault identification in continuous systems allowing mode changes while performing parameter identification.