Adaptive consensus of scale-free multi-agent system by randomly selecting links

ABSTRACT

This paper investigates an adaptive consensus problem for distributed scale-free multi-agent systems (SFMASs) by randomly selecting links, where the degree of each node follows a power-law distribution. The randomly selecting links are based on the assumption that every agent decides to select links among its neighbours according to the received data with a certain probability. Accordingly, a novel consensus protocol with the range of the received data is developed, and each node updates its state according to the protocol. By the iterative method and Cauchy inequality, the theoretical analysis shows that all errors among agents converge to zero, and in the meanwhile, several criteria of consensus are obtained. One numerical example shows the reliability of the proposed methods.

KEYWORDS:

• Scale-free multi-agent system
• discrete system
• probability connected
• selecting link
• adaptive consensus

Acknowledgements

The authors gratefully acknowledge the helpful comments and suggestions of the anonymous reviewers and the editor, which have improved the quality of this manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work has been supported by the Fund of Zhejiang Provincial Education Department [Y201533479]; and the cultivation Fund of Taizhou University [2015PY008].