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Dynamic Event-Triggered Bipartite Formation for MIMO Multiagent Systems With Quantized Data
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AI
DOI：10.1109/TCYB.2025.3614090.png)
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Abstract
En 中文
This article deals with fully distributed data-driven bipartite formation control for nonlinear discrete-time multi-input–multi-output multiagent systems (MASs) with unknown dynamics models and quantized information. Initially, a distributed combined measurement error function (DCMEF) is developed for MASs characterized by cooperative and competitive interactions. This function is designed to transform bipartite formation challenges into traditional consensus problems. Subsequently, a distributed compact form dynamic linearization model is established based on the designed DCMEF and input–output data of the MASs, eliminating the need for a strongly connected communication topology. Following this, a logarithmic quantization scheme and a dynamic event-triggered communication mechanism are devised to reduce the communication burden and enhance convergence speed. Finally, a data-driven fully distributed dynamic event-triggered bipartite formation control method is proposed, and its convergence is rigorously proven. Simulation studies and hardware experiments are conducted to validate the effectiveness of the proposed method.
Keywords:
Bipartite formation
data-driven
dynamic event-triggered
fully distributed control
quantization information
Journal
IF:
10.5
Papers:
1.1W
Citations:
5.0W
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