The optimization of consensus decision-making for a multi-microwave source system based on composite leader-follower clustering for intelligent agent-based joint heating temperature field
To address the issues of uneven temperature distribution and the difficulty of temperature control in microwave heating, a composite leader cluster consensus decision optimization strategy for multiple microwave source agents is proposed. This strategy aims to optimize the temperature field distribu...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
|
| Series: | Case Studies in Thermal Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X2401699X |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832573257614622720 |
|---|---|
| author | Biao Yang Baowei Song Cheng Cheng Youpeng Zhao Haiqin Yang Yuchen Li Zhongyi He |
| author_facet | Biao Yang Baowei Song Cheng Cheng Youpeng Zhao Haiqin Yang Yuchen Li Zhongyi He |
| author_sort | Biao Yang |
| collection | DOAJ |
| description | To address the issues of uneven temperature distribution and the difficulty of temperature control in microwave heating, a composite leader cluster consensus decision optimization strategy for multiple microwave source agents is proposed. This strategy aims to optimize the temperature field distribution and improve heating control accuracy. First, a distributed control framework for joint heating was established. Second, within this structure, multiple leader systems within the composite leader system were used for decision-making. Consensus decisions between multiple leader decision points were made through a weight allocation algorithm, achieving a dynamic balance between temperature control and temperature field optimization. Then, on the basis of the composite leader decision information, the feeding power of the microwave source cluster was coordinated via a consensus algorithm, achieving dynamic coordination and complementarity between the leader cluster and the follower cluster. Finally, the simulation results revealed that after adopting this strategy, the temperature control error rate ranged from 0.25% to 1.43%. Compared with a single leader decision system, the composite leader decision system improved the uniformity in the horizontal and vertical sections by 1% to 37% and 3.5% to 26.5%, respectively. Compared with traditional microwave heating methods, the uniformity in the horizontal and vertical sections was improved by 25.3% to 61.2% and 24.2% to 66.6%, respectively. These results verify that the proposed consistency heating strategy under composite leader consensus decision-making is feasible and efficient, achieving precise temperature control and optimization of the temperature field. |
| format | Article |
| id | doaj-art-f001832a84364c4ea76cf6e6a8b5d71a |
| institution | Kabale University |
| issn | 2214-157X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Case Studies in Thermal Engineering |
| spelling | doaj-art-f001832a84364c4ea76cf6e6a8b5d71a2025-02-02T05:27:10ZengElsevierCase Studies in Thermal Engineering2214-157X2025-02-0166105668The optimization of consensus decision-making for a multi-microwave source system based on composite leader-follower clustering for intelligent agent-based joint heating temperature fieldBiao Yang0Baowei Song1Cheng Cheng2Youpeng Zhao3Haiqin Yang4Yuchen Li5Zhongyi He6Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500, China; The Higher Educational Key Laboratory for Industrial Intelligence and Systems of Yunnan Province, Kunming University of Science and Technology, 650500, China; Yunnan Provincial Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming, 650500, China; Key Laboratory of Unconventional Metallurgy, Ministry of Education, Kunming University of Science and Technology, Kunming, 650093, China; Correspondence to: Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Jingming South Road 727, Kunming, 650500, China.Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500, China; The Higher Educational Key Laboratory for Industrial Intelligence and Systems of Yunnan Province, Kunming University of Science and Technology, 650500, ChinaFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500, China; The Higher Educational Key Laboratory for Industrial Intelligence and Systems of Yunnan Province, Kunming University of Science and Technology, 650500, ChinaFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500, China; The Higher Educational Key Laboratory for Industrial Intelligence and Systems of Yunnan Province, Kunming University of Science and Technology, 650500, ChinaFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500, China; The Higher Educational Key Laboratory for Industrial Intelligence and Systems of Yunnan Province, Kunming University of Science and Technology, 650500, ChinaFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500, China; The Higher Educational Key Laboratory for Industrial Intelligence and Systems of Yunnan Province, Kunming University of Science and Technology, 650500, ChinaFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500, China; The Higher Educational Key Laboratory for Industrial Intelligence and Systems of Yunnan Province, Kunming University of Science and Technology, 650500, ChinaTo address the issues of uneven temperature distribution and the difficulty of temperature control in microwave heating, a composite leader cluster consensus decision optimization strategy for multiple microwave source agents is proposed. This strategy aims to optimize the temperature field distribution and improve heating control accuracy. First, a distributed control framework for joint heating was established. Second, within this structure, multiple leader systems within the composite leader system were used for decision-making. Consensus decisions between multiple leader decision points were made through a weight allocation algorithm, achieving a dynamic balance between temperature control and temperature field optimization. Then, on the basis of the composite leader decision information, the feeding power of the microwave source cluster was coordinated via a consensus algorithm, achieving dynamic coordination and complementarity between the leader cluster and the follower cluster. Finally, the simulation results revealed that after adopting this strategy, the temperature control error rate ranged from 0.25% to 1.43%. Compared with a single leader decision system, the composite leader decision system improved the uniformity in the horizontal and vertical sections by 1% to 37% and 3.5% to 26.5%, respectively. Compared with traditional microwave heating methods, the uniformity in the horizontal and vertical sections was improved by 25.3% to 61.2% and 24.2% to 66.6%, respectively. These results verify that the proposed consistency heating strategy under composite leader consensus decision-making is feasible and efficient, achieving precise temperature control and optimization of the temperature field.http://www.sciencedirect.com/science/article/pii/S2214157X2401699XDistributed controlComposite leader systemIntelligent heating strategyConsensus tracking strategyTemperature field distribution optimization |
| spellingShingle | Biao Yang Baowei Song Cheng Cheng Youpeng Zhao Haiqin Yang Yuchen Li Zhongyi He The optimization of consensus decision-making for a multi-microwave source system based on composite leader-follower clustering for intelligent agent-based joint heating temperature field Case Studies in Thermal Engineering Distributed control Composite leader system Intelligent heating strategy Consensus tracking strategy Temperature field distribution optimization |
| title | The optimization of consensus decision-making for a multi-microwave source system based on composite leader-follower clustering for intelligent agent-based joint heating temperature field |
| title_full | The optimization of consensus decision-making for a multi-microwave source system based on composite leader-follower clustering for intelligent agent-based joint heating temperature field |
| title_fullStr | The optimization of consensus decision-making for a multi-microwave source system based on composite leader-follower clustering for intelligent agent-based joint heating temperature field |
| title_full_unstemmed | The optimization of consensus decision-making for a multi-microwave source system based on composite leader-follower clustering for intelligent agent-based joint heating temperature field |
| title_short | The optimization of consensus decision-making for a multi-microwave source system based on composite leader-follower clustering for intelligent agent-based joint heating temperature field |
| title_sort | optimization of consensus decision making for a multi microwave source system based on composite leader follower clustering for intelligent agent based joint heating temperature field |
| topic | Distributed control Composite leader system Intelligent heating strategy Consensus tracking strategy Temperature field distribution optimization |
| url | http://www.sciencedirect.com/science/article/pii/S2214157X2401699X |
| work_keys_str_mv | AT biaoyang theoptimizationofconsensusdecisionmakingforamultimicrowavesourcesystembasedoncompositeleaderfollowerclusteringforintelligentagentbasedjointheatingtemperaturefield AT baoweisong theoptimizationofconsensusdecisionmakingforamultimicrowavesourcesystembasedoncompositeleaderfollowerclusteringforintelligentagentbasedjointheatingtemperaturefield AT chengcheng theoptimizationofconsensusdecisionmakingforamultimicrowavesourcesystembasedoncompositeleaderfollowerclusteringforintelligentagentbasedjointheatingtemperaturefield AT youpengzhao theoptimizationofconsensusdecisionmakingforamultimicrowavesourcesystembasedoncompositeleaderfollowerclusteringforintelligentagentbasedjointheatingtemperaturefield AT haiqinyang theoptimizationofconsensusdecisionmakingforamultimicrowavesourcesystembasedoncompositeleaderfollowerclusteringforintelligentagentbasedjointheatingtemperaturefield AT yuchenli theoptimizationofconsensusdecisionmakingforamultimicrowavesourcesystembasedoncompositeleaderfollowerclusteringforintelligentagentbasedjointheatingtemperaturefield AT zhongyihe theoptimizationofconsensusdecisionmakingforamultimicrowavesourcesystembasedoncompositeleaderfollowerclusteringforintelligentagentbasedjointheatingtemperaturefield AT biaoyang optimizationofconsensusdecisionmakingforamultimicrowavesourcesystembasedoncompositeleaderfollowerclusteringforintelligentagentbasedjointheatingtemperaturefield AT baoweisong optimizationofconsensusdecisionmakingforamultimicrowavesourcesystembasedoncompositeleaderfollowerclusteringforintelligentagentbasedjointheatingtemperaturefield AT chengcheng optimizationofconsensusdecisionmakingforamultimicrowavesourcesystembasedoncompositeleaderfollowerclusteringforintelligentagentbasedjointheatingtemperaturefield AT youpengzhao optimizationofconsensusdecisionmakingforamultimicrowavesourcesystembasedoncompositeleaderfollowerclusteringforintelligentagentbasedjointheatingtemperaturefield AT haiqinyang optimizationofconsensusdecisionmakingforamultimicrowavesourcesystembasedoncompositeleaderfollowerclusteringforintelligentagentbasedjointheatingtemperaturefield AT yuchenli optimizationofconsensusdecisionmakingforamultimicrowavesourcesystembasedoncompositeleaderfollowerclusteringforintelligentagentbasedjointheatingtemperaturefield AT zhongyihe optimizationofconsensusdecisionmakingforamultimicrowavesourcesystembasedoncompositeleaderfollowerclusteringforintelligentagentbasedjointheatingtemperaturefield |