Yuxiao Lian , Baoyong Zhang , Deming Yuan , Yao Yao , Bo Song
{"title":"定向通信不平衡的异构线性多智能体网络的规定时间分布式资源分配算法","authors":"Yuxiao Lian , Baoyong Zhang , Deming Yuan , Yao Yao , Bo Song","doi":"10.1016/j.amc.2025.129498","DOIUrl":null,"url":null,"abstract":"<div><div>In this paper, a prescribed-time distributed algorithm is proposed to solve the resource allocation problem among the heterogeneous linear multi-agent systems over unbalanced directed networks. First, an estimator with prescribed-time convergence performance is designed to cope with the asymmetry of the unbalanced network topology. Then, a novel prescribed-time convergence result that features an adjustable convergence rate is developed. Based on this result, it is shown that the algorithm developed in this paper ensures the agents' outputs accurately reach the optimal solution within a prescribed-time and they are maintained at the optimum thereafter. Furthermore, a parameter selection rule is formulated to reflect the low conservatism of the algorithm. This indicates that the parameters affecting the convergence speed of the algorithm are not necessary to rely on the global information. Finally, the performance of the proposed algorithm is illustrated through simulations.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":"503 ","pages":"Article 129498"},"PeriodicalIF":3.5000,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prescribed-time distributed resource allocation algorithm for heterogeneous linear multi-agent networks with unbalanced directed communication\",\"authors\":\"Yuxiao Lian , Baoyong Zhang , Deming Yuan , Yao Yao , Bo Song\",\"doi\":\"10.1016/j.amc.2025.129498\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In this paper, a prescribed-time distributed algorithm is proposed to solve the resource allocation problem among the heterogeneous linear multi-agent systems over unbalanced directed networks. First, an estimator with prescribed-time convergence performance is designed to cope with the asymmetry of the unbalanced network topology. Then, a novel prescribed-time convergence result that features an adjustable convergence rate is developed. Based on this result, it is shown that the algorithm developed in this paper ensures the agents' outputs accurately reach the optimal solution within a prescribed-time and they are maintained at the optimum thereafter. Furthermore, a parameter selection rule is formulated to reflect the low conservatism of the algorithm. This indicates that the parameters affecting the convergence speed of the algorithm are not necessary to rely on the global information. Finally, the performance of the proposed algorithm is illustrated through simulations.</div></div>\",\"PeriodicalId\":55496,\"journal\":{\"name\":\"Applied Mathematics and Computation\",\"volume\":\"503 \",\"pages\":\"Article 129498\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2025-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Mathematics and Computation\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0096300325002243\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mathematics and Computation","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0096300325002243","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
Prescribed-time distributed resource allocation algorithm for heterogeneous linear multi-agent networks with unbalanced directed communication
In this paper, a prescribed-time distributed algorithm is proposed to solve the resource allocation problem among the heterogeneous linear multi-agent systems over unbalanced directed networks. First, an estimator with prescribed-time convergence performance is designed to cope with the asymmetry of the unbalanced network topology. Then, a novel prescribed-time convergence result that features an adjustable convergence rate is developed. Based on this result, it is shown that the algorithm developed in this paper ensures the agents' outputs accurately reach the optimal solution within a prescribed-time and they are maintained at the optimum thereafter. Furthermore, a parameter selection rule is formulated to reflect the low conservatism of the algorithm. This indicates that the parameters affecting the convergence speed of the algorithm are not necessary to rely on the global information. Finally, the performance of the proposed algorithm is illustrated through simulations.
期刊介绍:
Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results.
In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.