Observer-based fault diagnosis for a class of nonlinear systems

The focus of this paper is the detection and diagnosis of parameter faults in nonlinear systems. The novelty of this contribution is that it handles the nonlinear fault distribution function. Since such a fault distribution function depends not only on the inputs and outputs of the system but also on unmeasured states, it causes additional complexity in fault estimation. The proposed diagnostic tool is based on the adaptive observer technique. Under the Lipschitz condition, a fault detection observer and adaptive diagnosis observer are proposed. Then, relaxation of the Lipschitz requirement is proposed and the necessary modification to the diagnostic tool is presented. Finally, the example of a one-wheel model with lumped friction is presented to illustrate the applicability of the proposed diagnosis method.