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

Abstract

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.

Keywords:

• Bipartite consensus
• scaled consensus
• coopetition network
• high-order multi-agent system
• adaptive control

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant numbers 61473061, 61104104, 71503206].