Finite memory generalised state observer for failure detection in dynamic systems

To solve the fault detection and isolation problem, many techniques are based on state estimation. The divergence phenomenon of the state estimation error due to the accumulation of model uncertainties leads to the design of finite memory observer for both discrete and continuous time representations. Such observers are therefore more efficient for fault detection. This paper presents an extension of the finite memory observer so that both the input and the state of the system are estimated on a fixed number of measurements. The relevance is that the estimation can be performed even if the data are not given with the same sampling period. In addition, actuator and sensor fault detection and isolation can be performed within bank of observers driven by different subsets of input and output measurements. Further, a new residual can be defined so that the residual robustness to model uncertainties might be improved as it has already been shown and applied by Nuninger et al. (1997) within finite memory state estimation.