Discrete time-varying fault detection filter for non-uniformly sampled-data systems

This paper investigates the fault detection problem for non-uniformly sampled-data systems. No periodic assumption is made for the sampling instants. In contrast to most currently available results that are limited to strictly proper systems, measurement noises are considered. With the operators introduced to capture the inter-sampling behaviors of disturbances and faults, an offline fault detection algorithm is first derived to optimize the ratio-type design objective. It is then equivalently transformed into a recursive algorithm consisting of a discrete time-varying fault detection filter and the corresponding residual evaluation function. As repeated computation of the parity vectors is avoided, the proposed fault detection filter can help reduce the online computational burden with comparison to the existing parity relation based fault detection method.