Distributed Constraint Optimization with Flocking Behavior

This paper studies distributed optimization having flocking behavior and local constraint set. Multiagent systems with continuous-time and second-order dynamics are studied. Each agent has a local constraint set and a local objective function, which are known to only one agent. The objective is for...

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Main Authors: Zhengquan Yang, Qing Zhang, Zengqiang Chen
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2018/1579865
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author Zhengquan Yang
Qing Zhang
Zengqiang Chen
author_facet Zhengquan Yang
Qing Zhang
Zengqiang Chen
author_sort Zhengquan Yang
collection DOAJ
description This paper studies distributed optimization having flocking behavior and local constraint set. Multiagent systems with continuous-time and second-order dynamics are studied. Each agent has a local constraint set and a local objective function, which are known to only one agent. The objective is for multiple agents to optimize a sum of the local functions with local interaction and information. First, a bounded potential function to construct the controller is given and a distributed optimization algorithm that makes a group of agents avoid collisions during the evolution is presented. Then, it is proved that all agents track the optimal velocity while avoiding collisions. The proof of the main result is divided into three steps: global set convergence, consensus analysis, and optimal set convergence. Finally, a simulation is included to illustrate the results.
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id doaj-art-72fc21ed6f3d4bd0bcd7265577a0a3b7
institution OA Journals
issn 1076-2787
1099-0526
language English
publishDate 2018-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-72fc21ed6f3d4bd0bcd7265577a0a3b72025-08-20T02:06:27ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/15798651579865Distributed Constraint Optimization with Flocking BehaviorZhengquan Yang0Qing Zhang1Zengqiang Chen2College of Science, Civil Aviation University of China, Tianjin 300300, ChinaCollege of Science, Civil Aviation University of China, Tianjin 300300, ChinaDepartment of Automation, Nankai University, Tianjin 300071, ChinaThis paper studies distributed optimization having flocking behavior and local constraint set. Multiagent systems with continuous-time and second-order dynamics are studied. Each agent has a local constraint set and a local objective function, which are known to only one agent. The objective is for multiple agents to optimize a sum of the local functions with local interaction and information. First, a bounded potential function to construct the controller is given and a distributed optimization algorithm that makes a group of agents avoid collisions during the evolution is presented. Then, it is proved that all agents track the optimal velocity while avoiding collisions. The proof of the main result is divided into three steps: global set convergence, consensus analysis, and optimal set convergence. Finally, a simulation is included to illustrate the results.http://dx.doi.org/10.1155/2018/1579865
spellingShingle Zhengquan Yang
Qing Zhang
Zengqiang Chen
Distributed Constraint Optimization with Flocking Behavior
Complexity
title Distributed Constraint Optimization with Flocking Behavior
title_full Distributed Constraint Optimization with Flocking Behavior
title_fullStr Distributed Constraint Optimization with Flocking Behavior
title_full_unstemmed Distributed Constraint Optimization with Flocking Behavior
title_short Distributed Constraint Optimization with Flocking Behavior
title_sort distributed constraint optimization with flocking behavior
url http://dx.doi.org/10.1155/2018/1579865
work_keys_str_mv AT zhengquanyang distributedconstraintoptimizationwithflockingbehavior
AT qingzhang distributedconstraintoptimizationwithflockingbehavior
AT zengqiangchen distributedconstraintoptimizationwithflockingbehavior