Dynamic event-triggered state estimation for time-delayed spatial-temporal networks under encoding-decoding scheme

Sun, Jie; Shen, Bo; Liu, Yurong; Alsaadi, Fuad E.

doi:10.1016/j.neucom.2022.05.062

Cited by 4 publications

(2 citation statements)

References 49 publications

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“…Different from the SETS with the fixed triggering threshold, the DETS being capable of dynamically adjusting the triggering condition, is dependent on an adjustable auxiliary variable, thereby providing remarkable flexibility and further improving the resource‐utilization efficiency. So far, the DETS‐based state estimation problems for networked systems have drawn ever‐increasing research attention 17,18 . For example, the state estimation problem has been addressed in Reference 17 for the neural networks with nonhomogeneous under DETS.…”

Section: Introductionmentioning

confidence: 99%

“…So far, the DETS-based state estimation problems for networked systems have drawn ever-increasing research attention. 17,18 For example, the state estimation problem has been addressed in Reference 17 for the neural networks with nonhomogeneous under DETS. Therefore, the DETS will be deployed in communication channels to tackle the state estimation problem for time-varying CNs in this article, and the introduction of such a mechanism inevitably brings about the mathematical difficulty of incorporating the state estimation scheme.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic‐event‐based state estimation of complex networks against attacks and innovation outliers: The probability constraint case

Chen

Meng

et al. 2023

Intl J Robust & Nonlinear

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This article is devoted to the state estimation issue under probability constraint for a class of time-varying stochastic complex networks with uncertain inner couplings and cyber-attacks. To save the communication energy, the dynamic event-triggered strategy is deployed in each individual sensor-to-estimator channel to govern the data transmissions. A multi-attack model incorporating two different deception signals is considered to describe the phenomenon of randomly occurring cyber-attacks. The saturation-type function is involved to reduce the possible innovation outliers resulting from the hostile deception signals. A sufficient condition is first developed to guarantee the probability H ∞ performance constraint on estimation error dynamics over certain finite horizon, and then the suitable state estimator gains are derived by means of a set of matrix inequalities. Subsequently, a recursive algorithm is put forward for the addressed finite-horizon state estimator design problem. Finally, the validity of the proposed state estimation scheme is testified by a numerical example.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic‐event‐based state estimation of complex networks against attacks and innovation outliers: The probability constraint case

Chen

Meng

et al. 2023

Intl J Robust & Nonlinear

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Outlier‐resistant state estimation for complex networks with random false data injection attacks under encoding–decoding mechanism

Liu,

Hu,

Jia

et al. 2024

Adaptive Control & Signal

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SummaryThis article focuses on the outlier‐resistant state estimation problem for discrete time‐varying complex networks (TVCNs) affected by random false data injection attacks (FDIAs) under an encoding–decoding mechanism (EDM). From the perspective of information security, a uniform‐quantization‐based EDM is employed to encrypt the transmitted data. During the data transmission process, a set of independent random variables governed by Bernoulli distribution is introduced to characterize the occurrence of random FDIAs. For the purpose of alleviating the passive impact of potential measurement outliers, a saturation structure is adopted during the estimator design. The gain matrix is given by minimizing the upper bound of estimation error covariance. According to the stochastic analysis method, it is shown that the state estimation error is bounded exponentially in mean‐square sense by providing new sufficient condition. It should be noted that we make the first attempt to develop new outlier‐resistant state estimation method with performance evolution criterion in the time‐varying perspective for TVCNs with random FDIAs under EDM. Finally, a simulation example with comparative experiment is presented to illustrate the effectiveness of the newly presented outlier‐resistant estimation algorithm.

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Finite-horizon distributed set-membership filtering with dynamical bias and DoS attacks under binary encoding schemes

Song

Hou

et al. 2023

Information Sciences

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Dynamic event-triggered state estimation for time-delayed spatial-temporal networks under encoding-decoding scheme

Cited by 4 publications

References 49 publications

Dynamic‐event‐based state estimation of complex networks against attacks and innovation outliers: The probability constraint case

Dynamic‐event‐based state estimation of complex networks against attacks and innovation outliers: The probability constraint case

Outlier‐resistant state estimation for complex networks with random false data injection attacks under encoding–decoding mechanism

Finite-horizon distributed set-membership filtering with dynamical bias and DoS attacks under binary encoding schemes

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