Parity space hybrid system diagnosis under model uncertainty

Abstract

In this paper, diagnosis for hybrid systems using a parity space approach that considers model uncertainty is proposed. The hybrid diagnoser is composed of modules which carry out the mode recognition and diagnosis tasks both based on residuals generated using a model. Both tasks interact each other since the diagnosis module adapts himself according to the current mode of the hybrid system. Moreover, the methodology takes into account the parameter uncertainty using a passive robust strategy. An adaptive threshold for residual evaluation is generated and the parity space approach is used to design a set of residuals for each mode. The proposed fault diagnosis approach for hybrid systems is illustrated on a part of the Barcelona sewer network.