This technical note considers a consensus problem of high-order multiagent systems with antagonistic interactions and communication noises. The interaction network associated with the multiagent system is modeled by a signed graph (called coopetition network) and the agent dynamics is described by a general linear system. A novel stochastic-approximation based control strategy is designed for each agent by using the relative state information from its neighbors. Additionally, convergence of a consensus error system is analyzed by the stochastic stability theory. Finally, the effectiveness of our results is demonstrated by simulation.
- Communication noise
- coopetition network
- linear multiagent systems
- mean square bipartite consensus
- stochastic-approximation gain