Robust Consensus Analysis and Design under Relative State Constraints or Uncertainties
Abstract
This paper proposes a new approach to analyze and design distributed robust consensus control protocols for general linear leaderless multi-agent systems (MASs) in presence of relative-state constraints or uncertainties. First, we show that the MAS robust consensus under relative-state constraints or uncertainties is equivalent to the robust stability under state constraints or uncertainties of a transformed MAS. Next, the transformed MAS under state constraints or uncertainties is reformulated as a network of Lur'e systems. By employing S-procedure, Lyapunov theory, and Lasalle's invariance principle, a sufficient condition for robust consensus and the design of robust consensus controller gain are derived from solutions of a distributed LMI convex problem. Finally, numerical examples are introduced to illustrate the effectiveness of the proposed theoretical approach.
Cite
@article{arxiv.1605.03647,
title = {Robust Consensus Analysis and Design under Relative State Constraints or Uncertainties},
author = {Dinh Hoa Nguyen and Tatsuo Narikiyo and Michihiro Kawanishi},
journal= {arXiv preprint arXiv:1605.03647},
year = {2016}
}
Comments
submitted to IEEE Transactions on Automatic Control