Event-based fault detection for interval type-2 fuzzy systems with measurement outliers

Abstract

This paper investigates the event-based fault detection (FD) problem for a category of discrete-time interval type-2 fuzzy systems with measurement outliers. For the sake of decreasing the utilization of limited communication bandwidth, an event-based mechanism is introduced. Based on the saturation function technique, a novel event-based FD observer is first designed to reduce the influence of outliers in the dynamic systems. Then, on the basis of Lyapunov stability theory, sufficient conditions are provided to ensure that the error system satisfies the H∞ performance and the H∞ fault performance in different cases, respectively. In contrast to the existing event-based FD results, the false alarm, which is induced by measurement outliers, can be effectively avoided by the designed FD observer with saturation function. Lastly, some simulation results are given to verify the effectiveness of the method presented in this paper.

Dissipative fault detection for time‐delay nonlinear Markov jump systems with measurement outliers under stochastic communication protocol

“…Then, defining 16) is guaranteed by Θi,p j < 0 for ∀j ∈  i, . Therefore, we can deduce ( 16) from (42), which means the conclusion that the FD system ( 11) is stochastically stable and stochastically strictly (Q 1 , Q 2 , Q 3 )-𝛾 dissipative can be deduced from (42).…”

“…and other parameters are given as in Theorem 1. Furthermore, if the LMI (42) is feasible for any i ∈  , p ∈ , the FD filter matrix L f ,i,p can be obtained directly by solving the LMI. And the FD filter matrix K f ,i,p can be obtained as follows:…”

“…Step 2 ∶ Solve the LMI (42) with respect to P i,p > 0, S > 0, Ž > 0, R i,p > 0, Ŵ > 0, κ > 0, 𝛽 > 0, 𝜀 1 ≥ 0, and 𝜀 2 ≥ 0 for any i ∈  , p ∈ .…”

“…In Reference 41, the FD issue for T‐S fuzzy systems with measurement outliers has been discussed, in which the influence of measurement outliers has been reduced via imposing adaptive saturation constraints on the estimation error. Furthermore, the method of adopting adaptive saturation function to deal with measurement outliers has been extended to the FD of interval type‐2 fuzzy systems under event triggered mechanism in Reference 42. In the FD studies mentioned above, the augmented FD system has been required to meet $$$ {H}_{\infty } $$$ performance.…”

Fault detection filtering for continuous-time singular systems under a dynamic event-triggered mechanism

“…Therefore, it is particularly important to study how to detect faults in time when they occur. In order to tackle this problem, the method of fault detection has been established and has attracted a lot of attention in the past decades [19,38,3,11,17,7]. The basic principle of fault detection filtering (FDF) is to generate a residual signal using the filter structure and compare it with the detection threshold.…”