However, the adoption of increasingly aggressive manufacturing processes makes the memory sub-system particularly sensitive to faults.
Our focus is on the design of a fuzzy fault detection filter that is sensitive to faults but robust against unknown inputs.
It is the aim of a robust FD system to be sensitive to faults, such as this, while remaining insensitive to uncertainty and disturbances.
The generated residual signal is robust with respect to undesirable effects of unknown inputs and modelling errors but sensitive to faults.
The scheme is based on a bank of two observers aimed at generating a set of residuals sensitive to faults occurrence.
Hence, in the process of fault detection, residual generation is a very important step, based on this, there are many basic approaches are provided to generate robust residuals that are sensitive to faults, while insensitive to unknown input and noise.
To make the residual sensitive to faults and robust against disturbances, we develop a finite frequency H−∕H∞ design method based on a generalized Kalman Yakubovich Popov lemma for LPV descriptor systems.
The proposed residual generator has network-state dependent parameters, and it is designed to approach a reference residual model, such that the generated residuals are robust against system uncertainties and unknown inputs, and sensitive to faults.
