Mean-square bipartite consensus control for discrete-time multi-agent systems under cooperation-competition networks: A source binary encoding-decoding scheme

This paper focuses on the mean-square bipartite consensus control problem for a class of discrete-time multi-agent systems (DTMASs) with communication constraints under cooperation-competition networks. The data exchange between agents is facilitated by an allocation-based protocol, where the bits o...

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Vydáno v:	Neurocomputing (Amsterdam) Ročník 664; s. 132097
Hlavní autoři:	Zheng, Shaobo, Zhou, Lei
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.02.2026
Témata:	Bit-rate constraint Cooperation–competition network Source binary encoding-decoding scheme Time-varying control gain Cooperation–competition network Source binary encoding-decoding scheme Time-varying control gain Bit-rate constraint
ISSN:	0925-2312
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Popis
Shrnutí:	This paper focuses on the mean-square bipartite consensus control problem for a class of discrete-time multi-agent systems (DTMASs) with communication constraints under cooperation-competition networks. The data exchange between agents is facilitated by an allocation-based protocol, where the bits of each channel are limited at every instant. A source binary encoding-decoding scheme (SBEDS) is proposed to enable each agent to send messages subject to the bit-rate constraints. A new bipartite consensus control protocol is introduced to mitigate coding errors, with time-varying gains that satisfy the conditions of the stochastic approximation (SA) algorithm. The paper aims to reveal certain mean-square bipartite consensus conditions subject to communication constraints. To achieve this, the statistical properties of the aggregated error are derived. Subsequently, by employing the random matrix theory and Lyapunov function technique, a sufficient condition is established. Finally, the applications to the Kuramoto oscillator system and the affinity and social noise Hegselmann-Krause (ASNHK) model over cooperation-competition networks are studied to show the effectiveness of the proposed scheme.
ISSN:	0925-2312
DOI:	10.1016/j.neucom.2025.132097