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: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/6028054 |
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| _version_ | 1850229475884662784 |
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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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