Fault accommodation of a class of nonlinear dynamical systems using a learning approach

The paper presents a robust fault diagnosis scheme for detecting and accommodating faults occurring in a class of nonlinear multi-input multi-output dynamical systems. Changes in the system dynamics due to a fault are modeled as nonlinear functions of the control input and state variables. The fault function can model slowly developing (incipient) or abrupt faults, with each component of the fault vector being represented by a separate time profile. The stability of the robust fault accommodation scheme is established using Lyapunov redesign methods.