Problems related to fault detection of networked control systems (NCSs) with both uncertain time-varying delay and quantization error are studied in this paper. A novel model with the form of polytopic uncertainty is given to represent the influences of both the time-varying delay and the quantization error, and then the reference model based method is used to design the residual generator that is robust to both unknown network-induced delay and unknown inputs. A numerical example is also given to illustrate the merits of the presented method. The proposed method can be regarded as an extension of the authors' former work, which can only deal with time-varying delay.
D-statistic contribution analysis has been frequently used in practice for fault diagnosis.Existing algorithms for computing contributions to D-statistic tend to distribute cross-term contribution equally between two correlated variables.This leads to increased variance in contribution estimation and hence poor separability of faulty and normal variables.A new method for contribution calculation to D-statistic is proposed here which introduces a weighting scheme capable of distinguishing the contributions of two correlated variables.Simulation examples show that the proposed approach achieves improved resolution for distinguishing faulty and normal conditions.
