Robust consensus protocols of multi-agent systems with unknown but bounded measurement errors

Abstract

This paper revisits the consensus problem for multi-agent systems (MASs) in the presence of unknown but bounded (UBB) measurement errors. Unlike existing works, the proposed approach accommodations agents with different upper bounds for their measurement errors. A distributed estimation algorithm is employed to estimate the state differences between neighboring agents using the inaccurate state measurements. Building on this estimation algorithm, a distributed robust consensus protocol is developed. It is demonstrated that the proposed protocol drives the MAS to a neighborhood of consensus, effectively mitigating or even eliminating the influence of UBB measurement errors on multi-agent consensus. The analysis is further extended to address the positive consensus problem for MASs with UBB measurement errors. Finally, numerical simulations confirm the effectiveness of the proposed consensus protocols.