Input-output systems robust nonlinear fault diagnosis

Describes a fault diagnosis algorithm for a class of nonlinear dynamic systems with modeling uncertainties when not all states of the system are measurable. The main idea behind this approach is to monitor the plant for any off-nominal system behavior due to faults utilizing a nonlinear online approximator with adjustable parameters. A nonlinear estimation model and learning algorithm are described so that the online approximator provides an estimate of the fault. The robustness, sensitivity, stability and performance properties of the nonlinear fault diagnosis scheme are rigorously established under certain assumptions on the failure type.