2022
DOI: 10.1177/01423312221126233
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A non-uniform event-triggered distributed filtering scheme for discrete-time nonlinear systems over wireless sensor networks

Abstract: This paper investigates the distributed set-membership filtering problem for discrete-time nonlinear systems subject to one-sided Lipschitz (OSL) and quadratic inner-boundedness (QIB) constraints over wireless sensor networks (WSNs). The investigation takes into account both system and sensor nonlinearities under unknown but bounded (UBB) perturbations. Moreover, a novel non-uniform event-triggering condition is introduced to achieve resource conservation while maintaining filter accuracy. The proposed trigger… Show more

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Cited by 17 publications
(7 citation statements)
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“…Note that periodic DoS attacks are tackled in this paper. How to investigate the co-design of improved event-triggered protocols [12], [32], [33] and the…”
Section: Discussionmentioning
confidence: 99%
“…Note that periodic DoS attacks are tackled in this paper. How to investigate the co-design of improved event-triggered protocols [12], [32], [33] and the…”
Section: Discussionmentioning
confidence: 99%
“…The description of telecommunication exchanges and the criteria governing data flow in the consensus approach are based on multi-agent system (MAS) theory [94][95][96][97][98]. An essential challenge in the MAS consensus method is to develop a suitable control strategy that enables all units to converge on a single value.…”
Section: Consensus-based Techniquesmentioning
confidence: 99%
“…However, when the lag rises, the system gets unsteady. [98] and distribution of energy in order to achieve maximum efficiency and cost reduction, while simultaneously providing a dependable power supply [163].…”
Section: Future Developments In Mgs Controlmentioning
confidence: 99%
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“…Undoubtedly, the problem of fault identification becomes notably more challenging when confronted with systems exhibiting parametric uncertainties within the model, as the conventional residual generation for fault detection fails to account for these inherent uncertainties. Among the various analytical approaches, it is worth mentioning the incorporation of parity relations [ 17 ] and the implementation of Kalman or robust filters [ 18 20 ]. Nevertheless, the use of a mathematical model to execute these strategies can give rise to numerous difficulties, which arise from elements such as the intricate nature of the system, the large number of dimensions involved, the presence of nonlinear relationships, and the existence of uncertainties related to parameters.…”
Section: Introductionmentioning
confidence: 99%