Distributed Model Predictive Consensus of Constrained Heterogeneous Multiagent Systems

In this article, the consensus of constrained linear heterogeneous multiagent systems under prediction and optimization is investigated. By optimizing the consensus problems constrained to state equations and general linear constraints, two types of distributed analytical model predictive controllers are proposed. Furthermore, stability conditions for the two types of controllers are derived, in which a relationship between the communication topology and dynamics of heterogeneous agents is clarified. Simulation examples of networked heterogeneous agents illustrate the convergence and validity of the proposed controllers.

Automated summary

This article investigates the consensus of constrained linear heterogeneous multiagent systems under prediction and optimization. Two types of distributed analytical model predictive controllers are proposed by optimizing the consensus problems constrained to state equations and general linear constraints. Furthermore, stability conditions for the two types of controllers are derived, clarifying the relationship between the communication topology and dynamics of heterogeneous agents. Simulation examples of networked heterogeneous agents illustrate the convergence and validity of the proposed controllers.