Dynamic Event-Triggered Bipartite Formation for MIMO Multiagent Systems With Quantized Data
Authors: Zhao, H., Shan, J., Xu, D., Yu, H.
Journal: IEEE Transactions on Cybernetics
Publication Date: 01/01/2026
Volume: 56
Issue: 2
Pages: 619-630
eISSN: 2168-2275
ISSN: 2168-2267
DOI: 10.1109/TCYB.2025.3614090
Abstract: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.
Source: Scopus
Dynamic Event-Triggered Bipartite Formation for MIMO Multiagent Systems With Quantized Data.
Authors: Zhao, H., Shan, J., Xu, D., Yu, H.
Journal: IEEE Trans Cybern
Publication Date: 02/2026
Volume: 56
Issue: 2
Pages: 619-630
eISSN: 2168-2275
DOI: 10.1109/TCYB.2025.3614090
Abstract: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.
Source: PubMed