Constrained H-infinity Consensus with Nonidentical Constraints

TL;DR

This paper presents an improved distributed algorithm for achieving H-infinity consensus in multi-agent networks with nonidentical constraints, using linear matrix inequalities to ensure robustness against disturbances.

Contribution

It introduces a novel approach combining nonlinear output functions and LMIs for constrained consensus with nonidentical constraints.

Findings

Consensus achieved under certain LMI conditions

Enhanced robustness to disturbances demonstrated

Applicable to multi-agent systems with diverse constraints

Abstract

This note considers the constrained H-infinity consensus of multi-agent networks with nonidentical constraint sets. An improved distributed algorithm is adopted and a nonlinear controlled output function is defined to evaluate the effect of disturbances. Then, it is shown that the constrained H-infinity consensus can be achieved if some linear matrix inequality has positive solution.