Asymptotic consensus of multi-agent systems under binary-valued observations and observation uncertainty

DOI10.1016/j.sysconle.2023.105656OpenAlexW4388177164MaRDI QIDQ6131452

Chuiliu Kong, Ying Wang, Yanlong Zhao

Publication date: 5 April 2024

Published in: Systems \& Control Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sysconle.2023.105656

zbMATH Keywords

multi-agent systemsconsensus controlbinary-valued observationrecursive projection algorithmobservation uncertaintypolynomial-type variance

Mathematics Subject Classification ID

Stochastic approximation (62L20) Multi-agent systems (93A16) Consensus (93D50)

Cites Work

• Recursive identification of FIR systems with binary-valued outputs and communication channels
• System identification with quantized observations
• Identification of ARMA models using intermittent and quantized output observations
• Distributed recursive projection identification with binary-valued observations
• Recursive projection algorithm on FIR system identification with binary-valued observations
• Asymptotically efficient parameter estimation using quantized output observations
• Quantized consensus
• Projected gradient methods for linearly constrained problems
• Consensus Protocol for Multiagent Systems With Undirected Topologies and Binary-Valued Communications
• Quantized Identification With Dependent Noise and Fisher Information Ratio of Communication Channels
• Consensus of Multi-Agent Systems Under Binary-Valued Measurements and Recursive Projection Algorithm
• Coordination and Consensus of Networked Agents with Noisy Measurements: Stochastic Algorithms and Asymptotic Behavior
• System identification using binary sensors
• Coordination of groups of mobile autonomous agents using nearest neighbor rules
• Distributed Consensus With Limited Communication Data Rate
• Distributed Coordination of Multi-Agent Systems With Quantized-Observer Based Encoding-Decoding
• Identification of FIR systems with binary-valued observations against denial-of-service attacks

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