Adaptive bipartite consensus on coopetition networks

•Adaptive bipartite consensus problem is formulated for coopetition networks.•The second-order agent dynamics suffers from unknown time-varying disturbances.•A bridgebuilder agent is introduced to intervene the final consensus state.•Adaptive bipartite consensus strategy is designed for each agent.•Sufficient conditions are given for consensus convergence of the multi-agent system.

In this paper, a bipartite consensus tracking problem is considered for a group of autonomous agents on a coopetition network, on which the agents interact cooperatively and competitively simultaneously. The coopetition network involves positive and negative edges and is conveniently modeled by a signed graph. Additionally, the dynamics of all the agents are subjected to unknown disturbances, which are represented by linearly parameterized models. An adaptive estimation scheme is designed for each agent by virtue of the relative position measurements and the relative velocity measurements from its neighbors. Then a consensus tracking law is proposed for a new distributed system, which uses the relative measurements as the new state variables. The convergence of the consensus tracking error and the parameter estimation are analyzed even when the coopetition network is time-varying and no more global information about the bounds of the unknown disturbances is available to all the agents. Finally, some simulation results are provided to demonstrate the formation of the bipartite consensus on the coopetition network.