Pseudo multi-hop distributed consensus algorithm under directed topologies

Huanxin, Peng; Sheng, Andong; Wang, Wenkai

doi:10.1109/icarcv.2012.6485432

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…For large-scale complex networks, the convergence rate of the distributed consensus with quantized communication has to be considered. A fast second-order distributed consensus (the pseudo two-hop distributed consensus algorithm) is proposed in [9]. By utilizing the previous information of the non-adjacency nodes based on single-hop communication, the convergence rate of the pseudo two-hop distributed consensus algorithm is accelerated dramatically.…”

Section: Introductionmentioning

confidence: 99%

Fast second-order distributed consensus with adaptive quantization

Huanxin

Wang

2012

2012 Power Engineering and Automation Conference

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In order to improve the accuracy and the convergence rate of distributed consensus under quantized communication, in the paper, based on adaptive quantization scheme, we propose the fast second-order distributed consensus algorithm. We analyze the convergence performance. The fast second-order distributed consensus with adaptive quantization achieves a consensus in a mean square sense, and the consensus is equal to the average of the initial states. Simultaneously, Simulations are done about the fast second-order distributed consensus based on adaptive quantization. Results show that the fast second-order distributed consensus algorithm based on adaptive quantization can reach an average consensus, and its convergence rate is higher than that of the first-order adaptive quantized distributed consensus algorithm, moreover, the mean square errors are smaller within the finite steps. Keywords-distributed consensus; adaptive quantization; quantized communication; second-order algorithmI.

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Section: Introductionmentioning

confidence: 99%

Fast second-order distributed consensus with adaptive quantization

Huanxin

Wang

2012

2012 Power Engineering and Automation Conference

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“…Assuming ideal links and no quantization, the high-order distributed consensus without distortion in [6] is written by:…”

Section: High-order Distributed Consensus Algorithmmentioning

confidence: 99%

“…In the past ten years, the distributed consensus algorithm attracted the much attention [1][2][3][4][5][6]. In practical applications, the information exchange among the nodes of sensors network is based on digital communication, the impact of the quantization errors on the performance of the distributed consensus algorithms has to be considered.…”

Section: Introductionmentioning

confidence: 99%

Analysis on the High-order Distributed Consensus under Probabilistic Quantized Communication

Huanxin¹

2017

dtetr

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Abstract. Because the high-order distributed consensus algorithm utilizes the previous state values of non-adjacent nodes to accelerate the convergent rate, under the quantized communication, it means that the high-order distributed consensus algorithm utilizes the quantized information of more non-adjacent nodes, the performance of the high-order algorithm become very important under quantized communication. in the paper, the performance and the mean square errors of the high-order probabilistic quantization distributed consensus algorithm were analyzed. By analysis and simulation, the bigger the length of quantization message is, the better the performance is, and the smaller the square errors of the high-order algorithm is.

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γ-Adaptive consensus control for multi-agent systems with adjustable convergence speed

Shi

Zhang

et al. 2017

2017 36th Chinese Control Conference (CCC)

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Pseudo multi-hop distributed consensus algorithm under directed topologies

Cited by 4 publications

References 12 publications

Fast second-order distributed consensus with adaptive quantization

Fast second-order distributed consensus with adaptive quantization

Analysis on the High-order Distributed Consensus under Probabilistic Quantized Communication

γ-Adaptive consensus control for multi-agent systems with adjustable convergence speed

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