OCSYSYMay 12, 2016

Robust Consensus of Linear Multi-Agent Systems under Input Constraints or Uncertainties

arXiv:1605.03648h-index: 22
Originality Synthesis-oriented
AI Analysis

For researchers in multi-agent systems, this provides a method to handle input constraints/uncertainties in consensus control, but the approach is incremental.

This paper proposes a new approach for robust consensus control of linear leaderless multi-agent systems under input constraints or uncertainties, reformulating the problem as a network of Lur'e systems and deriving sufficient conditions via distributed LMI. A numerical example demonstrates effectiveness.

This paper proposes a new approach to analyze and synthesize robust consensus control laws for general linear leaderless multi-agent systems (MASs) subjected to input constraints or uncertainties. First, the MAS under input constraints or uncertainties is reformulated as a network of Lur'e systems. Next, two scenarios of communication topology are considered, namely undirected and directed cyclic structures. In each case, a sufficient condition for consensus and the design of consensus controller gain are derived from solutions of a distributed LMI convex problem. Finally, a numerical example is introduced to illustrate the effectiveness of the proposed theoretical approach.

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