A new robust on-line fault diagnosis for nonlinear difference-algebraic systems

A new robust online fault diagnosis method based on least squares estimation for nonlinear difference-algebraic systems (DAS) with uncertainties is proposed. Based on the known nominal model of DAS, it firstly constructs an auxiliary system consisting of a difference equation and an algebraic equation, then based on the relationship between the state deviation and the faults in the difference equation and the relationship between the algebraic variable deviation and the faults in the algebraic equation, it identifies the faults on-line through least squares estimation. This method can not only detect, isolate and identify faults for DAS, but also give the upper bound of the error of fault identification.