An event-triggered recursive state estimation approach for time-varying nonlinear complex networks with quantization effects

Rahimi, Farshad; Rezaei, Hossein

doi:10.1016/j.neucom.2020.09.074

Cited by 33 publications

(17 citation statements)

References 34 publications

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“…, pre-and post-multiplying Equation (52) with L i , then Equation ( 44) with w = 1 can be obtained based on Schur complement, the inequality Equation ( 44) with w = 2 can also be derived by following the same process, which imply that Equation ( 44) is equivalent to Equation (21) given in Theorem 1.…”

Section: Theorem 2 For Given Scalars 𝛼mentioning

confidence: 99%

Decentralized event‐triggered synchronization control for complex networks with nonperiodic DoS attacks

Song

Liu

et al. 2021

Intl J Robust & Nonlinear

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This article focuses on the issue of decentralized event-triggered synchronization control for complex networks (CNs) under nonperiodic denial-of-service (DoS) attacks. First, to alleviate the pressure on network bandwidth, a decentralized event-triggered scheme is employed at each coupled node to decide whether the synchronization signal is transmitted to the communication network. Then, an event-based synchronization error model is established for CNs under DoS attacks, where the communication network is assumed to be composed of multiple transmission channels and DoS attacks will independently compromise each of channels. Based on the constructed model, sufficient conditions that assuring the secure synchronization of the system are analyzed with the assistance of Lyapunov stability theory. Meanwhile, the synchronization controller gains are designed by solving a set of linear matrix inequalities. The efficiency of the study is finally validated by simulations. K E Y W O R D Scomplex networks (CNs), decentralized synchronization control, DoS attacks, event-triggered scheme INTRODUCTIONComplex networks (CNs) are now widely used to model many practical systems with large scale, such as food webs, subway, power grid and so forth. 1-3 A typical CN is generally composed by a number of nodes each of which represents a real individual and links denoting the relationships between different individuals. Given the architecture characteristic

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Section: Theorem 2 For Given Scalars 𝛼mentioning

confidence: 99%

Decentralized event‐triggered synchronization control for complex networks with nonperiodic DoS attacks

Song

Liu

et al. 2021

Intl J Robust & Nonlinear

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“…In the analysis of complex networks, both the dynamics of individual nodes and the coupling configuration between different nodes should be simultaneously taken into account. Until now, much research attention has been devoted to the synchronization [6], [42] and state estimation [12], [36] problems of complex networks. The FD problem for complex networks has mostly been investigated in the robust framework [21], [32], [46], [49] where the worst-case performance of the disturbance attenuation has been considered.…”

Section: Introductionmentioning

confidence: 99%

Joint State and Fault Estimation of Complex Networks Under Measurement Saturations and Stochastic Nonlinearities

Liu

Wang

Zou

et al. 2022

IEEE Trans. on Signal and Inf. Process. over Networks

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“…In previous work, 28 a distributed EKF problem has been studied for discrete-time nonlinear systems with multiple fading measurements and event-triggered communication scheme in both sensor-to-estimator and estimator-to-estimator channels. In previous work, 29 they have studied a scalable robust EKF for a class of discrete time-varying nonlinear complex networks with quantization effects and event-triggered communication. Recently, an event-triggered recursive distributed state estimation problem has been proposed for discrete time-varying nonlinear systems over sensor networks with time-varying topologies.…”

Section: Introductionmentioning

confidence: 99%

Event‐triggered resilient distributed extended Kalman filter with consensus on estimation

Rezaei

Ghorbani

2021

Intl J Robust & Nonlinear

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This study investigates the event-triggered resilient recursive distributed state estimation problem for discrete-time nonlinear systems over sensor networks.An event-triggered mechanism is employed to save the limited computation resource and network bandwidth while maintaining the desired performance. A resilient Extended Kalman Filter (EKF) with consensus on estimations is developed, and consensus is first achieved with respect to the prediction estimation. The accuracy of the computed estimation is then improved via two recursive equations. By adopting the structure of the EKF, the filter gains are determined in each sensor node via utilization of an upper bound for the cross-covariance, thereby resulting in a lower computational burden. The boundedness of the estimation errors is analyzed. Simulation results are reported to illustrate the effectiveness of the proposed distributed filter.

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An event-triggered recursive state estimation approach for time-varying nonlinear complex networks with quantization effects

Cited by 33 publications

References 34 publications

Decentralized event‐triggered synchronization control for complex networks with nonperiodic DoS attacks

Decentralized event‐triggered synchronization control for complex networks with nonperiodic DoS attacks

Joint State and Fault Estimation of Complex Networks Under Measurement Saturations and Stochastic Nonlinearities

Event‐triggered resilient distributed extended Kalman filter with consensus on estimation

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