Robust consensus analysis and design under relative state constraints or uncertainties

Dinh Hoa Nguyen, Tatsuo Narikiyo, Michihiro Kawanishi

    Research output: Contribution to journalArticlepeer-review

    22 Citations (Scopus)


    This paper proposes a novel approach to analyze and design distributed robust consensus control algorithms for general linear leaderless multiagent systems (MASs) subjected to relative-state constraints or uncertainties represented by a locally or a globally sector-bounded condition. First, we show that the MAS robust consensus design under relative-state constraints or uncertainties is equivalent to the robust stability design under state constraints or uncertainties of a transformed MAS, which has lower dimensions. Next, the transformed MAS under state constraints or uncertainties is reformulated as a networked Lur'e system. By employing the S-procedure and Lyapunov theory, sufficient conditions for robust consensus and the designs of robust consensus controller gain are derived from solutions of distributed linear matrix inequality (LMI) convex problems. Finally, numerical examples are introduced to illustrate the effectiveness of the proposed theoretical approach.

    Original languageEnglish
    Pages (from-to)1694-1700
    Number of pages7
    JournalIEEE Transactions on Automatic Control
    Issue number6
    Publication statusPublished - Jun 2018

    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering
    • Computer Science Applications
    • Electrical and Electronic Engineering


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