Consensus of heterogeneous multi-agent system with input constraints

Abstract

This work shows an approach to achieve output consensus among heterogeneous agents in a multi-agent environment where each agent is subject to input constraints. The communication among agents is described by a time-varying directed/undirected graph. The approach is based on the well-known Internal Model Principle which uses a specific class of unstable reference systems. One contribution of this work is the characterization of the maximal constraint admissible invariant set (MCAI) for the combined agent-reference system. Typically, MCAI sets do not exist for unstable systems. This work shows that for an important class of agent-reference systems that are unstable, MCAI exist and can be computed. This MCAI set is used in a novel Reference Governor, combined with a projected consensus algorithm, to achieve output consensus of all agents while satisfying constraints of each. An example is provided to illustrate the approach.