Distributed Secure Filtering for Discrete-Time Systems Under Round-Robin Protocol and Deception Attacks

Liu, Kun; Guo, Hang; Zhang, Qirui; Xia, Yuanqing

doi:10.1109/tcyb.2019.2897366

Cited by 57 publications

(14 citation statements)

References 24 publications

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“…At last, a numerical simulation has been given to verify the feasibility and usefulness of our designed fault estimation approach. The future research topics would be the extension of the main results obtained in this paper to (1) the system with communication protocols and (2) the time‐varying complex systems …”

Section: Resultsmentioning

confidence: 99%

Finite‐horizon fault estimation for time‐varying systems with multiple fading measurements under torus‐event–based protocols

Wei

Ding

et al. 2019

Intl J Robust & Nonlinear

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Summary In this paper, the issue of the finite‐horizon H∞ fault estimation is dealt with for a class of discrete time‐varying systems subject to randomly occurring faults and multiple fading measurements. The missing phenomena may occur in a random way from different sensors, which is represented by an individual stochastic variable meeting a certain probability distribution. Furthermore, in order to alleviate the communication burden, the torus‐event–based protocols are adopted to schedule the data transmissions only when some significant events occur. Our aim of the presented issue is to estimate the fault such that, with multiple fading measurements via the received information governed by torus‐event–based protocols, the H∞ index is satisfied over a given finite horizon. Sufficient conditions are obtained for the desired time‐varying estimator in terms of the technique of stochastic analysis and the methods of completing squares. The desired estimator gains are calculated by working out two backward recursive Riccati difference equations. Finally, a numerical simulation is given to verify the usefulness of our designed fault estimation approach.

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Section: Resultsmentioning

confidence: 99%

Finite‐horizon fault estimation for time‐varying systems with multiple fading measurements under torus‐event–based protocols

Wei

Ding

et al. 2019

Intl J Robust & Nonlinear

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“…Comparative simulation results have been reported to show that the averaged root mean square errors (RMSE) of estimation gets decreased by our method compared to a rival one in literature. The main results of this paper can be developed to the following issues in order to improve the proposed method in the future works: (1) consideration of the roundrobin protocol for reducing the data exchange between nodes [19], [33], (2) attachment of the gain variations that usually occur in the practical system because of computational or implementation uncertainties in the hardware [34], [35], (3) consideration of the issue that when data is exchanged among the sensors, due to the vulnerability of communication networks, the information can be overheard and modified by the adversary [36], [37], (4) consideration of the Fault Estimation [38] . Thus, based on the view of the author, considering the above topics can improve the performance of the proposed method in practical applications.…”

Section: Discussionmentioning

confidence: 99%

Scalable Distributed State Estimation for a Class of State-Saturated Systems Subject to Quantization Effects

Rezaei

Farnam²,

Rahimi

et al. 2021

IEEE Access

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This paper investigates the problem of a scalable distributed state estimation for a class of discrete time-variant systems with state-saturation, quantization effects, and two redundant channels over a sensor network. In transmission data from a sensor to its estimator, two phenomena are considered together. First, the data of each sensor is transmitted to its estimator through two redundant communication channels. Second, innovation data is quantized before being used by the estimator. These phenomena are beneficial in alleviating the negative effects on measurements and reducing the energy consumption and bandwidth. In the structure of proposed filter consensus is used on estimations in which consensus is first achieved on the prediction estimation, then the accuracy of computed estimation is improved by two recursive equations. The parameters of the proposed filter are obtained for each sensor node by employing an upper bound for common error covariance, therefore less computational burden is required. Eventually, the comparative simulation results are presented to show that our method has better performance compared with a rival one recently published.

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“…The RR protocol is another commonly used protocol, which allows only one node to communicate with its neighbors during scheduled time slots and therefore leads to bandwidth savings. Preliminary research on H ∞ consensus filtering can be found in [73] and, subsequently, has gained increasing attention by making use of the time-delay approach [44] as well as the periodic system analysis method [47,76,84]. For example, distributed set-membership filtering is addressed in [47] for multi-rate systems which are transformed into a traditional discrete-time system by means of lifting techniques.…”

Section: Basic Analysis Schemes and Research Developmentsmentioning

confidence: 99%

Distributed filtering of networked dynamic systems with non-Gaussian noises over sensor networks: A survey

Ding¹,

Han²,

Ge³

2020

Kybernetika

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Distributed Secure Filtering for Discrete-Time Systems Under Round-Robin Protocol and Deception Attacks

Cited by 57 publications

References 24 publications

Finite‐horizon fault estimation for time‐varying systems with multiple fading measurements under torus‐event–based protocols

Finite‐horizon fault estimation for time‐varying systems with multiple fading measurements under torus‐event–based protocols

Scalable Distributed State Estimation for a Class of State-Saturated Systems Subject to Quantization Effects

Distributed filtering of networked dynamic systems with non-Gaussian noises over sensor networks: A survey

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