Linear quadratic optimal consensus of discrete-time multi-agent systems with optimal steady state: A distributed model predictive control approach

Qishao Wang; Zhisheng Duan; Yuezu Lv; Qingyun Wang; Guanrong Chen

doi:10.1016/j.automatica.2021.109505

Linear quadratic optimal consensus of discrete-time multi-agent systems with optimal steady state: A distributed model predictive control approach

Qishao Wang, Zhisheng Duan^*, Yuezu Lv, Qingyun Wang, Guanrong Chen

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

47 Citations (Scopus)

Abstract

This paper develops a distributed model predictive control algorithm for linear quadratic optimal consensus of discrete-time multi-agent systems. The consensus state and control sequence are both optimized at every predictive step on a finite horizon and then implemented in the real system. The stability of the closed-loop system is analyzed, establishing a distributed consensus condition depending only on individual agent's local parameters. The consensus condition is then relaxed for controllable systems, making it easy to choose the weighted matrices and control period for each agent. The proposed algorithm is applied to the formation control of multi-vehicle systems verified by numerical simulations.

Original language	English
Article number	109505
Journal	Automatica
Volume	127
DOIs	https://doi.org/10.1016/j.automatica.2021.109505
Publication status	Published - May 2021
Externally published	Yes

Keywords

Distributed algorithm
Formation control
Model predictive control
Multi-agent systems
Optimal consensus

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10.1016/j.automatica.2021.109505

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title = "Linear quadratic optimal consensus of discrete-time multi-agent systems with optimal steady state: A distributed model predictive control approach",

abstract = "This paper develops a distributed model predictive control algorithm for linear quadratic optimal consensus of discrete-time multi-agent systems. The consensus state and control sequence are both optimized at every predictive step on a finite horizon and then implemented in the real system. The stability of the closed-loop system is analyzed, establishing a distributed consensus condition depending only on individual agent's local parameters. The consensus condition is then relaxed for controllable systems, making it easy to choose the weighted matrices and control period for each agent. The proposed algorithm is applied to the formation control of multi-vehicle systems verified by numerical simulations.",

keywords = "Distributed algorithm, Formation control, Model predictive control, Multi-agent systems, Optimal consensus",

author = "Qishao Wang and Zhisheng Duan and Yuezu Lv and Qingyun Wang and Guanrong Chen",

note = "Publisher Copyright: {\textcopyright} 2021 Elsevier Ltd",

year = "2021",

month = may,

doi = "10.1016/j.automatica.2021.109505",

language = "English",

volume = "127",

journal = "Automatica",

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T1 - Linear quadratic optimal consensus of discrete-time multi-agent systems with optimal steady state

T2 - A distributed model predictive control approach

AU - Wang, Qishao

AU - Duan, Zhisheng

AU - Lv, Yuezu

AU - Wang, Qingyun

AU - Chen, Guanrong

PY - 2021/5

Y1 - 2021/5

N2 - This paper develops a distributed model predictive control algorithm for linear quadratic optimal consensus of discrete-time multi-agent systems. The consensus state and control sequence are both optimized at every predictive step on a finite horizon and then implemented in the real system. The stability of the closed-loop system is analyzed, establishing a distributed consensus condition depending only on individual agent's local parameters. The consensus condition is then relaxed for controllable systems, making it easy to choose the weighted matrices and control period for each agent. The proposed algorithm is applied to the formation control of multi-vehicle systems verified by numerical simulations.

AB - This paper develops a distributed model predictive control algorithm for linear quadratic optimal consensus of discrete-time multi-agent systems. The consensus state and control sequence are both optimized at every predictive step on a finite horizon and then implemented in the real system. The stability of the closed-loop system is analyzed, establishing a distributed consensus condition depending only on individual agent's local parameters. The consensus condition is then relaxed for controllable systems, making it easy to choose the weighted matrices and control period for each agent. The proposed algorithm is applied to the formation control of multi-vehicle systems verified by numerical simulations.

KW - Distributed algorithm

KW - Formation control

KW - Model predictive control

KW - Multi-agent systems

KW - Optimal consensus

UR - http://www.scopus.com/inward/record.url?scp=85101416308&partnerID=8YFLogxK

U2 - 10.1016/j.automatica.2021.109505

DO - 10.1016/j.automatica.2021.109505

M3 - Article

AN - SCOPUS:85101416308

SN - 0005-1098

VL - 127

JO - Automatica

JF - Automatica

M1 - 109505

ER -

Linear quadratic optimal consensus of discrete-time multi-agent systems with optimal steady state: A distributed model predictive control approach

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Keywords

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