Fixed-Time Optimization of Perturbed Multi-Agent Systems under the Resource Constraints
In this paper, a novel fixed-time distributed optimization algorithm is proposed to solve the multi-agent collaborative optimization (MSCO) problem with local inequality constraints, global equation constraints and unknown disturbances. At first, a penalty function method is used to eliminate the lo...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/7/4527 |
| _version_ | 1797608310101245952 |
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| author | Bing Wang Fumian Wang Yuquan Chen Chen Peng |
| author_facet | Bing Wang Fumian Wang Yuquan Chen Chen Peng |
| author_sort | Bing Wang |
| collection | DOAJ |
| description | In this paper, a novel fixed-time distributed optimization algorithm is proposed to solve the multi-agent collaborative optimization (MSCO) problem with local inequality constraints, global equation constraints and unknown disturbances. At first, a penalty function method is used to eliminate the local inequality constraints and transform the original problem into a problem without local constraints. Then, a novel three-stage control scheme is designed to achieve a robust fixed-time convergence. In the first stage, a fixed-time reaching law is given to completely eliminate the effect of unknown disturbances with the aid of the integral sliding mode control method; in the second stage, a suitable interaction strategy is provided such that the whole system could satisfy the global constraints in fixed-time; in the third stage, a fixed-time gradient optimization algorithm of the multi-agent system is presented, with which the states of all the agents will converge to the minimum value of the global objective in a fixed-time. Finally, the effectiveness of the proposed control strategy is verified in the problem of wind farm co-generation with 60 wind turbines. |
| first_indexed | 2024-03-11T05:41:41Z |
| format | Article |
| id | doaj.art-31acb60379fb46b2b047679c30c0ad7c |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T05:41:41Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-31acb60379fb46b2b047679c30c0ad7c2023-11-17T16:21:38ZengMDPI AGApplied Sciences2076-34172023-04-01137452710.3390/app13074527Fixed-Time Optimization of Perturbed Multi-Agent Systems under the Resource ConstraintsBing Wang0Fumian Wang1Yuquan Chen2Chen Peng3Department of Automation, Hohai University, Nanjing 211100, ChinaDepartment of Automation, Hohai University, Nanjing 211100, ChinaDepartment of Automation, Hohai University, Nanjing 211100, ChinaDepartment of Automation, Hohai University, Nanjing 211100, ChinaIn this paper, a novel fixed-time distributed optimization algorithm is proposed to solve the multi-agent collaborative optimization (MSCO) problem with local inequality constraints, global equation constraints and unknown disturbances. At first, a penalty function method is used to eliminate the local inequality constraints and transform the original problem into a problem without local constraints. Then, a novel three-stage control scheme is designed to achieve a robust fixed-time convergence. In the first stage, a fixed-time reaching law is given to completely eliminate the effect of unknown disturbances with the aid of the integral sliding mode control method; in the second stage, a suitable interaction strategy is provided such that the whole system could satisfy the global constraints in fixed-time; in the third stage, a fixed-time gradient optimization algorithm of the multi-agent system is presented, with which the states of all the agents will converge to the minimum value of the global objective in a fixed-time. Finally, the effectiveness of the proposed control strategy is verified in the problem of wind farm co-generation with 60 wind turbines.https://www.mdpi.com/2076-3417/13/7/4527multi-agent systemsfixed-time convergencedisturbance rejectionpenalty function methoddistributed optimization |
| spellingShingle | Bing Wang Fumian Wang Yuquan Chen Chen Peng Fixed-Time Optimization of Perturbed Multi-Agent Systems under the Resource Constraints Applied Sciences multi-agent systems fixed-time convergence disturbance rejection penalty function method distributed optimization |
| title | Fixed-Time Optimization of Perturbed Multi-Agent Systems under the Resource Constraints |
| title_full | Fixed-Time Optimization of Perturbed Multi-Agent Systems under the Resource Constraints |
| title_fullStr | Fixed-Time Optimization of Perturbed Multi-Agent Systems under the Resource Constraints |
| title_full_unstemmed | Fixed-Time Optimization of Perturbed Multi-Agent Systems under the Resource Constraints |
| title_short | Fixed-Time Optimization of Perturbed Multi-Agent Systems under the Resource Constraints |
| title_sort | fixed time optimization of perturbed multi agent systems under the resource constraints |
| topic | multi-agent systems fixed-time convergence disturbance rejection penalty function method distributed optimization |
| url | https://www.mdpi.com/2076-3417/13/7/4527 |
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