Outlier‐resistant quantized control for T‐S fuzzy systems under multi‐channel‐enabled round‐robin protocol and deception attacks

Zha, Lijuan; Huang, Tao; Liu, Jinliang; Xie, Xiangpeng

doi:10.1002/rnc.6919

Cited by 4 publications

(1 citation statement)

References 40 publications

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“…In recent years, based on the T-S fuzzy model approach, the study on networked systems has also attracted attention and some important results have been achieved (see, e.g., [17][18][19][20] and references therein). Particularly, based on the T-S fuzzy model approach, the control problem of nonlinear networked systems with quantization was studied in [21][22][23][24][25][26] and the control problem of nonlinear networked systems subject to data packet dropouts was addressed in [27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Dissipative Fuzzy Filtering for Nonlinear Networked Systems with Dynamic Quantization and Data Packet Dropouts

Jing,

Lu,

2024

Mathematics

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This paper discusses the dissipative filtering problem for discrete-time nonlinear networked systems with dynamic quantization and data packet dropouts. The Takagi–Sugeno (T–S) fuzzy model is employed to approximate the considered nonlinear plant. Both the measurement and performance outputs are assumed to be quantized by the dynamic quantizers before being transmitted. Moreover, the Bernoulli stochastic variables are utilized to characterize the effects of data packet dropouts on the measurement and performance outputs. The purpose of this paper is to design full- and reduced-order filters, such that the stochastic stability and dissipative filtering performance for the filtering error system can be guaranteed. The collaborative design conditions for the desired filter and the dynamic quantizers are expressed in the form of linear matrix inequalities. Finally, simulation results are used to illustrate the feasibility of the proposed filtering scheme.

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Section: Introductionmentioning

confidence: 99%

Dissipative Fuzzy Filtering for Nonlinear Networked Systems with Dynamic Quantization and Data Packet Dropouts

Jing,

Lu,

2024

Mathematics

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Event‐based privacy‐preserving security consensus of multi‐agent systems with encryption–decryption mechanism

Liu,

Deng,

Zha

et al. 2024

Intl J Robust & Nonlinear

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The article concentrates on exploring the issue of privacy‐preserving sliding mode consensus of multi‐agent systems (MASs) with disturbance. An encryption and decryption algorithm has been proposed to address data security and privacy issues during data transmission. To optimize network resource allocation, a dynamic event‐triggering mechanism has been introduced, which reduces the number of encrypted data while saving the computation cost. The consensus performance based on the sliding mode control strategy is achieved when the reachability of the slide‐mode surface is guaranteed, and then the slide‐mode controller is developed. Finally, an empirical demonstration through a numerical example validates the efficacy of the proposed strategy.

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Privacy‐preserving‐based fuzzy filtering for nonlinear networked systems with adaptive‐event‐triggered mechanism and FDI attacks

Liu,

Tang,

Zha

et al. 2024

Intl J Robust & Nonlinear

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This article centers around the privacy‐preserving‐based secure filtering issue for interval type‐2 (IT‐2) fuzzy networked systems with false data injection (FDI) attacks. In order to achieve the goal of privacy preserving and significantly enhancing system security against potential eavesdropping threats, a novel encryption‐decryption mechanism (EDM) is adopted to safeguard the safety of signals across the network. The mechanism encrypts the transmitted signal by introducing artificial noise, secret key, and utilizing randomly selected nodes. This ensures that the actual transmitted data remains invisible to eavesdroppers while minimally the impact on the estimated performance of the proposed EDM. Given the network communication resources are becoming constrained due to the ever‐increasing network traffic, an adaptive event‐triggered mechanism (AETM) is employed to ease network congestion by an adaptively adjustable threshold. Then, various sufficient conditions have been outlined to ensure that the filtering error system meets the prescribed disturbance attenuation level. In the end, a numerical example is presented to evaluate both the precision and effectiveness of the developed algorithms.

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Outlier‐resistant quantized control for T‐S fuzzy systems under multi‐channel‐enabled round‐robin protocol and deception attacks

Cited by 4 publications

References 40 publications

Dissipative Fuzzy Filtering for Nonlinear Networked Systems with Dynamic Quantization and Data Packet Dropouts

Dissipative Fuzzy Filtering for Nonlinear Networked Systems with Dynamic Quantization and Data Packet Dropouts

Event‐based privacy‐preserving security consensus of multi‐agent systems with encryption–decryption mechanism

Privacy‐preserving‐based fuzzy filtering for nonlinear networked systems with adaptive‐event‐triggered mechanism and FDI attacks

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