Fault reconstruction in a class of nonlinear systems using inversion-based filter

Abstract

The article presents an approach for fault reconstruction in nonlinear systems. In addition to straightforward detection, fault reconstruction is also highly beneficial in directly isolating the faults by revealing which component is faulty. Initially an inversion-based fault reconstruction filter is introduced for nonlinear systems subject to an actuator or plant fault. If the system has fixed relative order with respect to the fault signal, the filter will reproduce the fault at its output. Then, a class of affine nonlinear systems is considered which is subject to unknown disturbances in addition to fault signals. In this case, for each fault the original system is transformed to a new form in which the proposed inversion-based filter can be applied for fault reconstruction. The transformation is done via a novel formulation on the observability concept in differential geometry. Reproducing the fault in the presence of unknown disturbances is main advantage of the proposed approach. To illustrate the effectiveness of the proposed methodology, simulation results are provided.