Characterisation of interval-observer fault detection and isolation properties using the set-invariance approach

Abstract

The aim of this paper is to provide a robust Fault Detection and Isolation (FDI) approach that combines the set-invariance approach with a zonotopic interval observer. The effect of the uncertainty is taken into account considering zonotopic-set representations in both the transient and steady states. The set-invariance approach is used to characterize the fault detectability and isolability properties in the steady-state operation of the system. In particular, the Minimum Detectable Fault (MDF) and the Minimum Isolable Fault (MIF) are characterized for several type of faults in separate formulations utilizing the integration of classical sensitivity analysis and set-invariance approaches. Finally, a simulation example based on a two-tanks system is employed to both illustrate and discuss the effectiveness of the proposed approach.

A Survey on Model-Based Fault Detection Techniques for Linear Time-Invariant Systems with Numerical Analysis

“…Those are a proportional-integral observer (Do et al, 2018;Yang et al, 2020), sliding mode observer ( Zhirabok et al, 2018;Zhang et al, 2019), interval observer (Pourasghar et al, 2020;Zammali et al 2020), and adaptive observer (Lijia et al, 2019;Perrin et al, 2004). These observers are designed to estimate the system output with minimum output estimation error and fast convergence speed.…”

Robust Sensor Fault Detection for Linear Parameter-Varying Systems using Interval Observer

“…The present paper focuses on the design of a TNL interval observer with L ∞ performance for robust sensor fault detection. The sensibility analysis of the proposed interval observer, characterized for example by the minimum detectable fault approach (Meseguer et al, 2010;Pourasghar et al, 2020), is therefore not addressed here and left to subsequent works.…”

Sensor fault detection for switched systems using interval observer with L∞ performance

“…In the presence of uncertainties coming either from external disturbances or from the mismatch between the model and the real system, interval observers have been proven to be effective in determining whether the system is faulty or not, since they have been successfully applied to several practical problems and can deal with large uncertainties [17,18,19,20]. In [17], an interval observer-based FD method is investigated for discrete-time linear parametervarying systems.…”