Multirate sampled data driven fast rate fault detection of dynamic systems

Multirate sampled data (MRSD) dynamic systems are abundant in modern engineering systems. The inconsistent sampling rates cause data asynchrony and alter system properties, negatively impacting fault diagnosis with delayed and missed detections. In this paper, a fast rate fault detection scheme for dynamic systems is proposed, which is directly driven by MRSD. Firstly, the lifting technique is employed to transform asynchronous MRSD into single but slow rate sampled data. An auxiliary lifted output is constructed to compute a parity vector via subspace identification, facilitating a multi-dimensional diagnostic observer satisfying the Luenberger conditions. Then a post filter addresses causality constraint, allowing fast rate residual generation. Further, a fast rate residual evaluation scheme is developed. The effectiveness and superiority of the proposed scheme are demonstrated by a heating, ventilation and air conditioning (HVAC) example.