Multiagent Consensus Tracking Control Over Asynchronous Cooperation-Competition Networks

In nature, populations of organisms (e.g., wolves) exhibit a remarkable ability to coordinate their group actions, such as hunting prey or evading predators, despite the coexistence of cooperative and competitive interactions among individuals. Motivated by this intriguing phenomenon, this article investigates the cooperative consensus tracking control problem of multiagent systems (MASs) over cooperation-competition networks with asynchronous communications. That is, all followers can simultaneously achieve trajectory tracking of the leader agent, even if there exist competitive interactions between the followers and the leader. To portray the cooperation and competition level among agents, a new distance-based weight function is designed, which is more flexible than the fixed weight values in existing research works. Theoretically, the sufficient conditions for achieving consensus tracking control are obtained based on the convergence analysis method of infinite products of super-stochastic matrices. Finally, some numerical simulations are given to verify the effectiveness of the proposed consensus tracking control scheme.