Exponential convergence of distributed optimization for heterogeneous linear multi-agent systems over unbalanced digraphs

In this work we study a distributed optimal output consensus problem for heterogeneous linear multi-agent systems over unbalanced directed networks where the agents aim to reach consensus with the purpose of minimizing the sum of private smooth costs. Based on output feedback, a distributed continuo...

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Main Authors: Li, Li, Yu, Yang, Li, Xiuxian, Xie, Lihua
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/163542
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1635422022-12-08T08:41:08Z Exponential convergence of distributed optimization for heterogeneous linear multi-agent systems over unbalanced digraphs Li, Li Yu, Yang Li, Xiuxian Xie, Lihua School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Distributed Optimization Multi-Agent Systems In this work we study a distributed optimal output consensus problem for heterogeneous linear multi-agent systems over unbalanced directed networks where the agents aim to reach consensus with the purpose of minimizing the sum of private smooth costs. Based on output feedback, a distributed continuous time control law is proposed by using the proportional–integral (PI) control technique. Under the assumption that the global cost function satisfies the restricted secant inequality condition, the designed controller can achieve convergence exponentially in an unbalanced and strongly connected network. Furthermore, to remove the requirement of continuous communications, a sampling-based event-triggered algorithm with a lower bound of the communication interval is provided, which also converges exponentially. Two simulation examples are given to verify the proposed control algorithms. Ministry of Education (MOE) This research was supported by the National Natural Science Foundation of China under Grant 62003243, 72171172, Basic Science Centre Program by National Natural Science Foundation of China under grant 62088101, Ministry of Education of Republic of Singapore under Grant AcRF TIER 1-2019-T1-001-088 (RG72/19) , the Shanghai Municipal Commission of Science and Technology, China No. 19511132100, 19511132101, the Shang-hai Municipal Science and Technology Major Project, China, No. 2021SHZDZX0100, and National Key R&D Program of China, No. 2018YFE0105000, 2018YFB1305304. 2022-12-08T08:41:08Z 2022-12-08T08:41:08Z 2022 Journal Article Li, L., Yu, Y., Li, X. & Xie, L. (2022). Exponential convergence of distributed optimization for heterogeneous linear multi-agent systems over unbalanced digraphs. Automatica, 141, 110259-. https://dx.doi.org/10.1016/j.automatica.2022.110259 0005-1098 https://hdl.handle.net/10356/163542 10.1016/j.automatica.2022.110259 2-s2.0-85130198291 141 110259 en AcRF TIER 1-2019-T1-001-088 (RG72/19) Automatica © 2022 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Distributed Optimization
Multi-Agent Systems
spellingShingle Engineering::Electrical and electronic engineering
Distributed Optimization
Multi-Agent Systems
Li, Li
Yu, Yang
Li, Xiuxian
Xie, Lihua
Exponential convergence of distributed optimization for heterogeneous linear multi-agent systems over unbalanced digraphs
description In this work we study a distributed optimal output consensus problem for heterogeneous linear multi-agent systems over unbalanced directed networks where the agents aim to reach consensus with the purpose of minimizing the sum of private smooth costs. Based on output feedback, a distributed continuous time control law is proposed by using the proportional–integral (PI) control technique. Under the assumption that the global cost function satisfies the restricted secant inequality condition, the designed controller can achieve convergence exponentially in an unbalanced and strongly connected network. Furthermore, to remove the requirement of continuous communications, a sampling-based event-triggered algorithm with a lower bound of the communication interval is provided, which also converges exponentially. Two simulation examples are given to verify the proposed control algorithms.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Li, Li
Yu, Yang
Li, Xiuxian
Xie, Lihua
format Article
author Li, Li
Yu, Yang
Li, Xiuxian
Xie, Lihua
author_sort Li, Li
title Exponential convergence of distributed optimization for heterogeneous linear multi-agent systems over unbalanced digraphs
title_short Exponential convergence of distributed optimization for heterogeneous linear multi-agent systems over unbalanced digraphs
title_full Exponential convergence of distributed optimization for heterogeneous linear multi-agent systems over unbalanced digraphs
title_fullStr Exponential convergence of distributed optimization for heterogeneous linear multi-agent systems over unbalanced digraphs
title_full_unstemmed Exponential convergence of distributed optimization for heterogeneous linear multi-agent systems over unbalanced digraphs
title_sort exponential convergence of distributed optimization for heterogeneous linear multi-agent systems over unbalanced digraphs
publishDate 2022
url https://hdl.handle.net/10356/163542
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