Bipartite containment tracking over switching signed networks

L Chen, L Shi, G Qiu, J Shao, Y Cheng - Information Sciences, 2022 - Elsevier
L Chen, L Shi, G Qiu, J Shao, Y Cheng
Information Sciences, 2022Elsevier
This study is dedicated to the problem of bipartite containment tracking associated with
leader–follower multiagent systems (MASs) with generic linear dynamics over switching
signed networks. In particular, the considered signed networks are not only allowed to be
structurally balanced, but also structurally unbalanced, which are more appropriate
descriptions for a class of real-life networks including antagonistic interactions. First, an
approach based on augmented digraph is put forward, under which it transforms the initial …
Abstract
This study is dedicated to the problem of bipartite containment tracking associated with leader–follower multiagent systems (MASs) with generic linear dynamics over switching signed networks. In particular, the considered signed networks are not only allowed to be structurally balanced, but also structurally unbalanced, which are more appropriate descriptions for a class of real-life networks including antagonistic interactions. First, an approach based on augmented digraph is put forward, under which it transforms the initial MAS into an augmented system through an effective parameter selection scheme. Then, the convergence of the developed augmented system is analyzed by calculating the product convergence matrix of infinite sub-stochastic matrices. Finally, the behavior of bipartite containment tracking is performed under the connectivity condition that for each follower there exists a directed path rooted at the leaders in the union of the signed digraphs associated with specified time intervals. The effectiveness of the presented general connectivity condition for bipartite containment tracking performance is illustrated by means of several simulation tests.
Elsevier
Showing the best result for this search. See all results