DocumentCode :
80281
Title :
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
Link To Document :
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