Event-Triggered Adaptive Dynamic Programming Consensus Tracking Control for Discrete-Time Multiagent Systems

This paper proposes a novel adaptive dynamic programming (ADP) approach to address the optimal consensus control problem for discrete-time multiagent systems (MASs). Compared with the traditional optimal control algorithms for MASs, the proposed algorithm is designed on the basis of the event-trigge...

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Main Authors: Yuyang Zhao, Xiaolin Dai, Dawei Gong, Xinzhi Lv, Yang Liu
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2022/6028054
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author Yuyang Zhao
Xiaolin Dai
Dawei Gong
Xinzhi Lv
Yang Liu
author_facet Yuyang Zhao
Xiaolin Dai
Dawei Gong
Xinzhi Lv
Yang Liu
author_sort Yuyang Zhao
collection DOAJ
description This paper proposes a novel adaptive dynamic programming (ADP) approach to address the optimal consensus control problem for discrete-time multiagent systems (MASs). Compared with the traditional optimal control algorithms for MASs, the proposed algorithm is designed on the basis of the event-triggered scheme which can save the communication and computation resources. First, the consensus tracking problem is transferred into the input-state stable (ISS) problem. Based on this, the event-triggered condition for each agent is designed and the event-triggered ADP is presented. Second, neural networks are introduced to simplify the application of the proposed algorithm. Third, the stability analysis of the MASs under the event-triggered conditions is provided and the estimate errors of the neural networks’ weights are also proved to be ultimately uniformly bounded. Finally, the simulation results demonstrate the effectiveness of the event-triggered ADP consensus control method.
format Article
id doaj-art-2aca34ffe0d14d5287a84143a3faf9ce
institution OA Journals
issn 1099-0526
language English
publishDate 2022-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-2aca34ffe0d14d5287a84143a3faf9ce2025-08-20T02:04:13ZengWileyComplexity1099-05262022-01-01202210.1155/2022/6028054Event-Triggered Adaptive Dynamic Programming Consensus Tracking Control for Discrete-Time Multiagent SystemsYuyang Zhao0Xiaolin Dai1Dawei Gong2Xinzhi Lv3Yang Liu4School of Mechanical and Electrical EngineeringSchool of Mechanical and Electrical EngineeringSchool of Mechanical and Electrical EngineeringScience and Technology on Reactor System Design Technology LaboratorySchool of Mechanical and Electrical EngineeringThis paper proposes a novel adaptive dynamic programming (ADP) approach to address the optimal consensus control problem for discrete-time multiagent systems (MASs). Compared with the traditional optimal control algorithms for MASs, the proposed algorithm is designed on the basis of the event-triggered scheme which can save the communication and computation resources. First, the consensus tracking problem is transferred into the input-state stable (ISS) problem. Based on this, the event-triggered condition for each agent is designed and the event-triggered ADP is presented. Second, neural networks are introduced to simplify the application of the proposed algorithm. Third, the stability analysis of the MASs under the event-triggered conditions is provided and the estimate errors of the neural networks’ weights are also proved to be ultimately uniformly bounded. Finally, the simulation results demonstrate the effectiveness of the event-triggered ADP consensus control method.http://dx.doi.org/10.1155/2022/6028054
spellingShingle Yuyang Zhao
Xiaolin Dai
Dawei Gong
Xinzhi Lv
Yang Liu
Event-Triggered Adaptive Dynamic Programming Consensus Tracking Control for Discrete-Time Multiagent Systems
Complexity
title Event-Triggered Adaptive Dynamic Programming Consensus Tracking Control for Discrete-Time Multiagent Systems
title_full Event-Triggered Adaptive Dynamic Programming Consensus Tracking Control for Discrete-Time Multiagent Systems
title_fullStr Event-Triggered Adaptive Dynamic Programming Consensus Tracking Control for Discrete-Time Multiagent Systems
title_full_unstemmed Event-Triggered Adaptive Dynamic Programming Consensus Tracking Control for Discrete-Time Multiagent Systems
title_short Event-Triggered Adaptive Dynamic Programming Consensus Tracking Control for Discrete-Time Multiagent Systems
title_sort event triggered adaptive dynamic programming consensus tracking control for discrete time multiagent systems
url http://dx.doi.org/10.1155/2022/6028054
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AT xiaolindai eventtriggeredadaptivedynamicprogrammingconsensustrackingcontrolfordiscretetimemultiagentsystems
AT daweigong eventtriggeredadaptivedynamicprogrammingconsensustrackingcontrolfordiscretetimemultiagentsystems
AT xinzhilv eventtriggeredadaptivedynamicprogrammingconsensustrackingcontrolfordiscretetimemultiagentsystems
AT yangliu eventtriggeredadaptivedynamicprogrammingconsensustrackingcontrolfordiscretetimemultiagentsystems