Multi-Agent Bipartite Containment over Time-Varying Structurally Balanced Networks

This paper proposes a new model and its analysis results for time-varying structurally balanced networks. Through model transformations, the system stability problem is converted into the problem of product convergence of infinite sub-stochastic matrices (PCISM). Further, by constructing a new digraph for each interaction topology, the problem of PCISM can be handled by virtue of the properties of row-stochastic matrices. When all leaders belong to only one of the two subgroups, it is shown that the followers that are in the same subgroup as the leaders gradually enter the convex hull formed by the leaders' states, while the others gradually enter the convex hull formed by the leaders' sign-inverted states. And when both subgroups contain leaders, a sufficient algebraic graph condition is established to ensure that all followers can enter the convex hull consisting of the leaders' states and sign-inverted states together. Moreover, it is also found that the followers keep active after entering the convex hulls. Finally, the bipartite containment performance is verified by a simulation test.