Distributed Quantized Consensus With Recursive Channel Filters Over Directed Networks

Lina Rong

doi:10.1109/TCSII.2021.3099875

Distributed Quantized Consensus With Recursive Channel Filters Over Directed Networks

2022-03-01

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DOI：10.1109/TCSII.2021.3099875

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This brief investigates the quantized consensus in discrete-time multi-agent systems over directed networks with limited bandwidths of communication channels and limited capacities of physical memories. A dynamic consensus protocol based on the first-order recursive channel filter is proposed. Several conditions for preserving the asymptotic consensus are obtained, which are dependent on the filter parameters, the sampling period and the topologies of the communication networks. Then, by describing the closed-loop multi-agent system via a higher-order state-space model, the effects of the probabilistic quantization are analyzed. We prove that the quantized consensus is reached under the proposed protocol with quantized communications. Moreover, the distributed PI based protocol is discussed as a special case of the proposed dynamic protocol.

Keywords:

Protocols

Transfer functions

Quantization (signal)

Probabilistic logic

Bandwidth

Eigenvalues and eigenfunctions

Directed graphs

Probabilistic quantization

directed communication network

recursive filter

consensus

Distributed Quantized Consensus With Recursive Channel Filters Over Directed Networks

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