Robust Consensus Analysis and Design under Relative State Constraints or Uncertainties
It addresses robust consensus for general linear leaderless MASs with constraints/uncertainties, but the approach is incremental, combining existing techniques (S-procedure, Lyapunov theory) without new fundamental insights.
This paper proposes a method to analyze and design robust consensus protocols for multi-agent systems under relative-state constraints or uncertainties, deriving sufficient conditions via a distributed LMI convex problem. Numerical examples demonstrate effectiveness.
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.