A Distributed Fault Detection Filtering Approach for a Class of Interconnected Continuous-Time Nonlinear Systems

This paper develops a filtering approach for distributed fault detection of a class of interconnected continuous-time nonlinear systems with modeling uncertainties, disturbances and measurement noise. A distributed fault detection scheme and the corresponding adaptive thresholds are designed based on filtering certain signals so that the effect of the measurement noise and of the disturbances is attenuated, allowing for the design of less conservative thresholds. A key novelty of the proposed work is that a general class of filters can be embedded into the design of the residual and threshold signals in a way that takes advantage of the filtering noise suppression properties. The analysis of the proposed distributed fault detection scheme shows that the derived thresholds guarantee that there are no false alarms and characterizes quantitatively the class of detectable faults. Further rigorous detectability analysis provides results regarding the magnitude of the detectable faults, an upper bound on the detection time and the relation of the detection time with respect to the order and pole locations of the filters used. Simulation results illustrate the proposed distributed fault filtering approach.