Adaptive scaled consensus control of coopetition networks with high-order agent dynamics

In this paper, we consider both bipartite consensus and scaled consensus control of high-order multi-agent systems with antagonistic interactions and unknown disturbances. The interaction topology associated with the multi-agent system is described by a coopetition network and modelled by a signed graph. Linearly parameterised approaches are used to model the unknown disturbances. For the bipartite consensus problem, a distributed adaptive state-feedback controller is designed for each agent. For the scaled consensus problem, a distributed adaptive controller is designed for each agent by using a projection mechanism. The convergence of the bipartite consensus errors and the scaled consensus errors is analysed with the help of a Lyapunov function method and the Barbalat's Lemma. Some simulation results are provided to demonstrate the effectiveness of the proposed adaptive control strategies.