Distributed Consensus of Nonlinear Multi-Agent Systems With Mismatched Uncertainties and Unknown High-Frequency Gains (Extended Version)

TL;DR

This paper proposes a novel distributed consensus algorithm for nonlinear multi-agent systems with mismatched uncertainties and unknown high-frequency gains, requiring minimal neighbor information, and guarantees asymptotic consensus and bounded signals.

Contribution

It introduces a new consensus method that only uses output information and handles complex uncertainties in nonlinear multi-agent systems.

Findings

Achieves asymptotic consensus in complex nonlinear systems

Ensures all signals remain bounded under the proposed control

Validated through rigorous theoretical analysis and simulations

Abstract

This brief addresses the distributed consensus problem of nonlinear multi-agent systems under a general directed communication topology. Each agent is governed by higher-order dynamics with mismatched uncertainties, multiple completely unknown high-frequency gains, and external disturbances. The main contribution of this brief is to present a new distributed consensus algorithm, enabling the control input of each agent to require minimal information from its neighboring agents, that is, only their output information. To this end, a dynamic system is explicitly constructed for each agent to generate a reference output. Theoretical and simulation verifications of the proposed algorithm are rigorously studied to ensure that asymptotic consensus can be achieved and that all closed-loop signals remain bounded.