Observer-based non-fragile <i>H</i><sub>∞</sub>-consensus control for multi-agent systems under deception attacks

Zhang, Jinnan; Song, Jinbo; Li, Jia-hui; Han, Fei; Zhang, Hongbin

doi:10.1080/00207721.2021.1884917

Cited by 38 publications

(6 citation statements)

References 54 publications

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“…Experiment results have shown that the proposed DOTLF outperforms some selected PLD methods under both normal and fault conditions. In the future, we aim to 1) optimize the source domain data to efficiently transfer detection knowledge [10], [19], [48], [55], [57]; and 2) design an advanced control strategy to further improve the detection accuracy and detection rate of the TL-LSTM-Ri-based PLD method [18], [21], [28], [50], [60].…”

Section: Discussionmentioning

confidence: 99%

A Novel Deep Offline-to-Online Transfer Learning Framework for Pipeline Leakage Detection With Small Samples

Wang

Liu

et al. 2023

IEEE Trans. Instrum. Meas.

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In this paper, a two-stage deep offline-to-online transfer learning framework (DOTLF) is proposed for longdistance pipeline leakage detection (PLD). At the offline training stage, a feature transfer-based long short-term memory network with regularization information (TL-LSTM-Ri) is developed where a maximum mean discrepancy regularization term is employed to extract domain-invariant features and an adjacentbias-corrected regularization term is introduced to extract early fault features from pipeline samples under different scenarios. At the online detection stage, the trained TL-LSTM-Ri is employed for motion prediction so as to monitor the operating condition of the pipeline in real time. To demonstrate its application potential, the DOTLF is successfully applied to handle the PLD problem on the long-distance oil-gas pipeline data. Experimental results demonstrate the effectiveness of the proposed DOTLF for realtime PLD under real-world scenarios.

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Section: Discussionmentioning

confidence: 99%

A Novel Deep Offline-to-Online Transfer Learning Framework for Pipeline Leakage Detection With Small Samples

Wang

Liu

et al. 2023

IEEE Trans. Instrum. Meas.

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“…In the context of state estimation for NCSs, it is often the case that the designed estimator gains cannot be exactly implemented due to various factors such as the aging of the devices, the finite word length in digital systems and the analogue‐digital conversion, and even a small fluctuation of the estimator gain could lead to dramatic deterioration of the algorithm performance. As such, the so‐called non‐fragile estimation problem has aroused much interest with several descriptions proposed on gain variations which include the norm‐bounded uncertainties 37,38 and the stochastic variables (with bounded variance) 39,40 . For instance, in Reference 40, the gain variations have been reflected in the estimator gains to model the computation/execution error, and the distributed resilient scheme has been developed to jointly estimate the actuator fault and the system state for a class of complex networks.…”

Section: Introductionmentioning

confidence: 99%

A non‐fragile approach to fault estimation for a class of multi‐rate systems under binary encoding schemes

Hou,

Wang,

Shen

et al. 2023

Intl J Robust & Nonlinear

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This article is concerned with the non‐fragile fault estimation issue for a class of multi‐rate systems under binary encoding schemes (BES). A specific dynamics relationship with zero second‐order difference is employed to characterize the evolution of the actuator fault. The signal communication is regulated by the BESs, where the resulting random bit errors are characterized by a certain stochastic noise. The aim of this article is to design a fault estimator such that the estimation error dynamics is exponentially ultimately bounded in mean square. First, an equivalent single‐rate system is formulated via the lifting technique. Then, by virtue of the stochastic analysis method and the matrix inequality approach, sufficient conditions are developed to ensure the existence of the desired fault estimator. Finally, the effectiveness of the proposed estimator design strategy is testified through a simulation example.

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“…In addition, in the above researches of containment control, the information communication are known as ideal. However, due to the openness and interconnectedness, communication channels between agents are vulnerable to various cyber attacks [22,23], for example, denial-of-service (DoS) attacks [24,25], and deception attacks [26,27]. When DoS attacks occur in MASs, the information communication between agents will be blocked [28,29], and when deception attacks occur in MASs, the authenticity and integrity of the information will be tampered with or destructed [30,31].…”

Section: Introductionmentioning

confidence: 99%

Event‐triggered containment control for multi‐agent systems under hybrid cyber attacks

Zhu

Liu

Zhang

et al. 2023

Asian Journal of Control

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This paper studies event‐triggered containment control problem of multi‐agent systems (MASs) under deception attacks and denial‐of‐service (DoS) attacks. First, to save limited network resources, an event‐triggered mechanism is proposed for MASs under hybrid cyber attacks. Different from the existing event‐triggered mechanisms, the negative influences of deception attacks and DoS attacks are considered in the proposed triggering function. The communication frequencies between agents are reduced. Then, based on the proposed event‐triggered mechanism, a corresponding control protocol is proposed to ensure that the followers will converge to the convex hull formed by the leaders under deception attacks and DoS attacks. Compared with the previous researches about containment control, in addition to hybrid cyber attacks being considered, the nonlinear functions related to the states of the agents are applied to describe the deception attack signals in the MAS. By orthogonal transformation of deception attack signals, the containment control problem under deception attacks and DoS attacks is reformulated as a stability problem. Then, the sufficient conditions on containment control can be obtained. Finally, a set of simulation example is used to verify the effectiveness of the proposed method.

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Observer-based non-fragile H_∞-consensus control for multi-agent systems under deception attacks

Cited by 38 publications

References 54 publications

A Novel Deep Offline-to-Online Transfer Learning Framework for Pipeline Leakage Detection With Small Samples

A Novel Deep Offline-to-Online Transfer Learning Framework for Pipeline Leakage Detection With Small Samples

A non‐fragile approach to fault estimation for a class of multi‐rate systems under binary encoding schemes

Event‐triggered containment control for multi‐agent systems under hybrid cyber attacks

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Observer-based non-fragile H∞-consensus control for multi-agent systems under deception attacks

Cited by 38 publications

References 54 publications

A Novel Deep Offline-to-Online Transfer Learning Framework for Pipeline Leakage Detection With Small Samples

A Novel Deep Offline-to-Online Transfer Learning Framework for Pipeline Leakage Detection With Small Samples

A non‐fragile approach to fault estimation for a class of multi‐rate systems under binary encoding schemes

Event‐triggered containment control for multi‐agent systems under hybrid cyber attacks

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Observer-based non-fragile H_∞-consensus control for multi-agent systems under deception attacks