Event-triggered distributed state estimation for a class of time-varying systems over sensor networks with redundant channels

Dong, Hongli; Bu, Xianye; Hou, Nan; Liu, Yurong; Alsaadi, Fuad E.; Hayat, Tasawar

doi:10.1016/j.inffus.2016.12.005

Cited by 88 publications

(54 citation statements)

References 41 publications

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“…In this section, by means of the vector dissipation theory, 12,13,34 sufficient conditions will be established for guaranteeing that the error dynamics (7) satisfies the H ∞ -consensus performance criterion (8).…”

Section: Resultsmentioning

confidence: 99%

“…The following theorem provides sufficient criterion to guarantee the stochastic vector dissipative-like property of system (10), which further infers the desired performance (8) for the error dynamics (7). Theorem 1.…”

Section: Definitionmentioning

confidence: 99%

“…Then, the locally augmented dynamics (10) is stochastic vector dissipative-like over the finite horizon  with respect to the vector supply rate S( k , k , k ). Moreover, the error dynamics (7) satisfies the H ∞ -consensus performance criterion (8).…”

Section: Definitionmentioning

confidence: 99%

“…Then, the error dynamics (7) satisfies the H ∞ -consensus performance constraint (8). Moreover, the filter gains L i,k and K ij,k are given as follows:…”

Section: Theoremmentioning

confidence: 99%

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Local design of distributed H_∞‐consensus filtering over sensor networks under multiplicative noises and deception attacks

Han

Dong

Wang

et al. 2019

Intl J Robust & Nonlinear

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Summary This paper is concerned with the local design of the distributed H∞‐consensus filtering problem for a class of discrete time‐varying systems subject to both multiplicative noises and deception attacks over sensor networks. The target plant and the measuring sensors are disturbed by multiplicative noises with known statistics. The malicious signal involved in deception attacks is constrained by a specific sector‐like bounded condition, which reflects certain tolerable bound on the difference between the attack signal and the true signal. Attention is paid to the design of filter gains for guaranteeing a desirable filtering performance that simultaneously characterizes the filtering accuracy and the consensus requirement. To handle the proposed filtering problem, the supply rate function is firstly chosen for each node and then the dissipation matrix is constructed as a column substochastic matrix based on the stochastic vector dissipation theory. Subsequently, sufficient conditions by means of recursive linear matrix inequalities are presented for each node such that the filtering error and the consensus error satisfy the desirable H∞‐consensus performance index over a finite horizon. Finally, an illustrative simulation is presented to demonstrate the effectiveness of the proposed filter strategy.

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Section: Resultsmentioning

confidence: 99%

Section: Definitionmentioning

confidence: 99%

Section: Definitionmentioning

confidence: 99%

“…Then, the error dynamics (7) satisfies the H ∞ -consensus performance constraint (8). Moreover, the filter gains L i,k and K ij,k are given as follows:…”

Section: Theoremmentioning

confidence: 99%

See 2 more Smart Citations

Local design of distributed H_∞‐consensus filtering over sensor networks under multiplicative noises and deception attacks

Han

Dong

Wang

et al. 2019

Intl J Robust & Nonlinear

Self Cite

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show abstract

“…In networked systems, the limited bandwidth of communication channel leads to several inevitable network‐induced phenomena, which could seriously deteriorate the system performances such as communication delays, missing measurements or packet dropouts, and randomly occurring nonlinearities . The communication delay has been often considered as a deterministic phenomenon that is not realistic.…”

Section: Introductionmentioning

confidence: 99%

Robust distributedH_∞filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays

Hedayati

Rahmani

2019

Intl J Robust & Nonlinear

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Summary In this paper, the problem of robust distributed H∞ filtering is investigated for state‐delayed discrete‐time linear systems over a sensor network with multiple fading measurements, random time‐varying communication delays, and norm‐bounded uncertainties in all matrices of the system. The diagonal matrices, whose elements are individual independent random variables, are utilized to describe the multiple fading measurements. Furthermore, the Bernoulli‐distributed white sequences are introduced to model the random occurrence of time‐varying communication delays. In the proposed filtering approach, the stability of the estimation error system is first shown by the Lyapunov stability theory and the H∞ performance is then achieved using a linear matrix inequality method. Finally, two numerical examples are given to show the effectiveness and performance of the proposed approach.

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Hybrid‐triggered fault detection filter design for networked Takagi–Sugeno fuzzy systems subject to persistent heavy noise disturbance

2021

Adaptive Control & Signal

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Summary In the network environment, the single time‐triggered scheme wastes limited bandwidth resources due to all the sampled data are transmitted to the networks, and the single event‐triggered scheme may increase system error because of ignoring factors such as changes in network utilization. To reduce the design conservatism, this paper is concerned with the hybrid‐triggered L1 fault detection filter design for a class of nonlinear networked control systems (NCSs) described by Takagi–Sugeno (T‐S) fuzzy model. Taking the effects of time‐triggered scheme and event‐triggered scheme into consideration simultaneously, we construct a fuzzy fault detection system. New results on stability and L1 performance are proposed for fuzzy fault detection system by exploiting the Lyapunov–Krasovskii functional and by means of the integral inequality method. Specially, attention is focused on the design of fault detection filter that guarantees a prescribed L1 noise attenuation level γ. Finally, two examples are presented to demonstrate the effectiveness of the proposed method.

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Event-triggered distributed state estimation for a class of time-varying systems over sensor networks with redundant channels

Cited by 88 publications

References 41 publications

Local design of distributed H_∞‐consensus filtering over sensor networks under multiplicative noises and deception attacks

Local design of distributed H_∞‐consensus filtering over sensor networks under multiplicative noises and deception attacks

Robust distributedH_∞filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays

Hybrid‐triggered fault detection filter design for networked Takagi–Sugeno fuzzy systems subject to persistent heavy noise disturbance

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Event-triggered distributed state estimation for a class of time-varying systems over sensor networks with redundant channels

Cited by 88 publications

References 41 publications

Local design of distributed H∞‐consensus filtering over sensor networks under multiplicative noises and deception attacks

Local design of distributed H∞‐consensus filtering over sensor networks under multiplicative noises and deception attacks

Robust distributedH∞filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays

Hybrid‐triggered fault detection filter design for networked Takagi–Sugeno fuzzy systems subject to persistent heavy noise disturbance

Contact Info

Product

Resources

About

Local design of distributed H_∞‐consensus filtering over sensor networks under multiplicative noises and deception attacks

Local design of distributed H_∞‐consensus filtering over sensor networks under multiplicative noises and deception attacks

Robust distributedH_∞filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays