Resilient Consensus Through Event-Based Communication

Wang, Yuan; Ishii, Hideaki

doi:10.1109/tcns.2019.2924235

Cited by 60 publications

(45 citation statements)

References 40 publications

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“…The resilient consensus algorithms developed in this paper follow the basic approach from [5,6,16]. We present two resilient algorithms that can be seen as extensions of our recent work [25], which dealt with the real-valued states case. The main difference in the algorithms is that those for the quantized case are based on randomization due to the use of the probabilistic quantizer.…”

Section: Definition 23 (F-total)mentioning

confidence: 99%

An event‐triggered approach to quantized resilient consensus

Wang

Ishii

2019

Intl J Robust & Nonlinear

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We consider an event-triggered update scheme for the problem of multi-agent consensus in the presence of faulty and malicious agents within the network. In particular, we focus on the case where the agents take integer (or quantized) values. To keep the regular agents from being affected by the behavior of faulty agents, algorithms of the mean subsequence reduced (MSR) type are employed, where neighbors taking extreme values are ignored in the updates. Different from the real-valued case, the quantized version requires the update rule to be randomized. We characterize the error bound on the achievable level of consensus among the agents as well as the necessary structure for the network in terms of the notion of robust graphs. We verify via a numerical example the effectiveness of the proposed algorithms. Copyright c

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Section: Definition 23 (F-total)mentioning

confidence: 99%

An event‐triggered approach to quantized resilient consensus

Wang

Ishii

2019

Intl J Robust & Nonlinear

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“…It was proved that the resilient consensus can be ensured if the communication topology satisfies a newly proposed graphic condition (f + 1, f + 1)-robustness/(2f + 1, 1)-robustness. From then on, the resilient consensus problem has been explored in different contexts, including double-integrator dynamics [30], communication delays [28], time-varying topologies [34], asynchronous networks [33], event-triggered communications [35], quantization [29], and differential privacy requirements [36]. All of the above-mentioned works on resilient consensus require the same graphic conditions as [32], where the highly connected communication topology is required.…”

Section: Introductionmentioning

confidence: 99%

Resilient Delayed Impulsive Control for Consensus of Multiagent Networks Subject to Malicious Agents

Zhai

Liu

Guan

2022

IEEE Trans. Cybern.

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Impulsive control is widely applied to achieve the consensus of multiagent networks (MANs). It is noticed that malicious agents may have adverse effects on the global behaviors, which, however, are not taken into account in the literature. In this study, a novel delayed impulsive control strategy based on sampled data is proposed to achieve the resilient consensus of MANs subject to malicious agents. It is worth pointing out that the proposed control strategy does not require any information on the number of malicious agents, which is usually required in the existing works on resilient consensus. Under appropriate control gains and sampling period, a necessary and sufficient graphic condition is derived to achieve the resilient consensus of the considered MAN. Finally, the effectiveness of the resilient delayed impulsive control is well demonstrated via simulation studies.

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“…For the networked systems, typical tasks, e.g., consensus [1], [2] and formation [3], [4], have been well studied, whereas here, we consider a different task, namely distributed spatial filtering (DSF). In this task, the nodes obtain signal values with a desired spatial frequency characteristic from given ones only through local communications.…”

Section: Introductionmentioning

confidence: 99%

Distributed Spatial Filtering Over Networked Systems

Izumi

Katayama

Xin

et al. 2021

IEEE Control Syst. Lett.

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This study concerns distributed spatial filtering over networked systems, i.e., transforming signal values given for nodes to those with a desired spatial frequency characteristic via a distributed computation. An existing filtering algorithm can achieve only low-pass filter characteristics, which limits its range of applications. To address this limitation, we extend the aforementioned filtering algorithm using an additional design parameter. We then present a characterization of all the realizable filter characteristics as a necessary and sufficient condition for achieving distributed spatial filtering. As a result, it is shown that the extended algorithm increases the range of the realizable filter characteristics. The proposed method is verified not only by simulation but also by denoising experiments for a real sensor network. The results show that the proposed method effectively reduces spatial noise and achieves higher performance than an average consensus algorithm and an average filter.

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Resilient Consensus Through Event-Based Communication

Cited by 60 publications

References 40 publications

An event‐triggered approach to quantized resilient consensus

An event‐triggered approach to quantized resilient consensus

Resilient Delayed Impulsive Control for Consensus of Multiagent Networks Subject to Malicious Agents

Distributed Spatial Filtering Over Networked Systems

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