Distributed Consensus of Multi-Agent Systems With Input Constraints: A Model Predictive Control Approach

Author

Zhaomeng Cheng ; Hai-Tao Zhang ; Ming-Can Fan ; Guanrong Chen

Author_Institution

State Key Lab. of Digital Manuf. Equip. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China

Volume

62

Issue

3

fYear

2015

fDate

Mar-15

Firstpage

825

Lastpage

834

Abstract

The discrete-time double-integrator consensus problem is addressed for multi-agent systems with directed switching proximity topologies and input constraints. Some model predictive control protocols are developed to achieve stable consensus under the condition that the proximity graph has a directed spanning tree and the sampling period is sufficiently small. Moreover, the control horizon is extended to larger than one, which endows sufficient degrees of freedom to accelerate the convergence to consensus. Numerical simulations are conducted to show the effectiveness of the control algorithm.

Keywords

discrete time systems; distributed control; integration; multi-agent systems; multi-robot systems; predictive control; trees (mathematics); control algorithm; control horizon; directed spanning tree; directed switching proximity topology; discrete-time double-integrator consensus problem; distributed consensus; input constraints; model predictive control approach; multi-agent systems; numerical simulation; proximity graph; sampling period; Convergence; Multi-agent systems; Predictive control; Protocols; Stacking; Topology; Vectors; Consensus; input constraint; predictive control; switching interaction network;

fLanguage

English

Journal_Title

Circuits and Systems I: Regular Papers, IEEE Transactions on

Publisher

ieee

ISSN

1549-8328

Type

jour

DOI

10.1109/TCSI.2014.2367575

Filename

6977999