Event-triggered fault detection for linear stochastic systems

Yu, Jinyong; Ning, Zhaoke; Liu, Yu

doi:10.1177/0142331217722195

Cited by 5 publications

(4 citation statements)

References 35 publications

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“…Furthermore, the time‐delay phenomenon caused by the limitation of signal transmission speed and network bandwidth has also been addressed in this paper, which makes the proposed fault detection method suitable for more general systems. In addition, the fault detection issue has also been studied in the works of Yu et al 48 and Ning et al 49 for Itô‐type stochastic system and nonlinear stochastic system under the static event‐triggered strategy, respectively, and the stability criteria guaranteeing the mean‐square asymptotic stability of the systems have been given. However, as we stated earlier, the asymptotic stability cannot describe the transient performance of the system in a certain period of time.…”

Section: Implementation Of Fault Detection Algorithmmentioning

confidence: 99%

Finite‐time fault detection for discrete nonlinear systems with time‐varying delays under the dynamic event‐triggered mechanism

Chen

et al. 2022

Intl J Robust & Nonlinear

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This article is concerned with the finite‐time fault detection (FTFD) problem for discrete networked systems subject to nonlinearities and time‐varying delays under the dynamic event‐triggered mechanism. The dynamic event‐based communication scheme is adopted to improve the efficiency of the bandwidth utilization, reduce the transmission of redundant signals and decrease the transmission pressure of the network. Then, by constructing a new Lyapunov functional and utilizing the appropriate inequality techniques, some sufficient conditions are derived under which the addressed augmented system achieves the finite‐time stability and attains a satisfactory H∞$$ {H}_{\infty } $$ performance index. Additionally, the expression forms of the fault detection filter (FDF) parameters are presented based on the solutions to certain matrix inequalities. In the end, a numerical simulation is employed to demonstrate the effectiveness and feasibility of the proposed FTFD strategy.

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Section: Implementation Of Fault Detection Algorithmmentioning

confidence: 99%

Finite‐time fault detection for discrete nonlinear systems with time‐varying delays under the dynamic event‐triggered mechanism

Chen

et al. 2022

Intl J Robust & Nonlinear

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“…Remark 4. If the degree of Ω ( x ( t ) ) is zero, Ω ( x ( t ) ) is reduced to a constant quadratic matrix Ω and the event-triggered scheme is reduced to the ones given by Yu et al (2018) and Liu et al (2016).…”

Section: System Formulationmentioning

confidence: 99%

Polynomial fault detection filter design under adaptive event-triggered scheme via line-integral Lyapunov functions

Ding

Liu

Yang

2021

Transactions of the Institute of Measurement and Control

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This paper investigates the problem of polynomial fault detection filter design under an adaptive event-triggered scheme for continuous-time networked polynomial fuzzy model–based (PFMB) systems considering network transmission delays. The proposed adaptive polynomial event-triggered scheme is checked only at the sampling instant to eliminate the Zeno behavior as well as save the network bandwidth. With the consideration of the mismatched membership functions (MFs), the asynchronous problem between the physical plant and the polynomial fault detection filter (PFDF) is examined. A Lyapunov–Krasovskii (L-K) function is introduced to deal with the time delays caused by the network transmission and the zero-order holder (ZOH), and a proper line-integral Lyapunov function is also introduced to reduce the conservation of the design constraints, whose analytical procedure is rule-dependent. The design constraints are given in the form of sum of squares (SOS) to keep the PFMB fault detection system asymptotically stable with [Formula: see text] performance [Formula: see text]. Finally, an inverted pendulum example together with a numerical example is given to verify the effectiveness and superiority of the proposed scheme in terms of transfer rate and conservatism.

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“…The fault detection mechanism can detect whether the fault occurs by generating a residual signal via the measurement output. At present, there are many methods to detect various fault signals (see Cheng et al, 2022; Jan et al, 2021; Ju et al, 2021; Li et al, 2019; Liu et al, 2021a; Yu et al, 2017). For example, Zhang and Fang (2011) studied the problem of robust fault detection for nonlinear systems with distributed delay.…”

Section: Introductionmentioning

confidence: 99%

Networked fault detection for fuzzy systems using a quantizer with event-triggered strategy

Chen,

Cui,

Sun

et al. 2023

Transactions of the Institute of Measurement and Control

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This paper concerns with the problem of fault detection for networked fuzzy systems. Considering the digital communication channel, quantization is adopted to make the data transmission feasible and the induced data distortion is converted into a bounded uncertain term. For the purpose of saving network resources, a new quantizer with an event-triggered strategy is designed to reduce the length and the number of the transmitted data packets, simultaneously. In the process of stability analysis, the T-S fuzzy model approach is employed to approximate the nonlinear networked system, and a more flexible fuzzy design method is presented to get the fault detection filter which can detect the sensor fault in the presence of external disturbance. And sufficient conditions are constructed to guarantee the stability of the filter error system in terms of linear matrix inequalities. Finally, the simulation example is given to verify the feasibility of the method.

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Event-triggered fault detection for linear stochastic systems

Cited by 5 publications

References 35 publications

Finite‐time fault detection for discrete nonlinear systems with time‐varying delays under the dynamic event‐triggered mechanism

Finite‐time fault detection for discrete nonlinear systems with time‐varying delays under the dynamic event‐triggered mechanism

Polynomial fault detection filter design under adaptive event-triggered scheme via line-integral Lyapunov functions

Networked fault detection for fuzzy systems using a quantizer with event-triggered strategy

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