{"title":"基于聚合和固定方法的多智能体网络一致性分析。","authors":"Wenjun Xiong, Daniel W C Ho, Zidong Wang","doi":"10.1109/TNN.2011.2157938","DOIUrl":null,"url":null,"abstract":"<p><p>In this paper, the consensus problem of multiagent nonlinear directed networks (MNDNs) is discussed in the case that a MNDN does not have a spanning tree to reach the consensus of all nodes. By using the Lie algebra theory, a linear node-and-node pinning method is proposed to achieve a consensus of a MNDN for all nonlinear functions satisfying a given set of conditions. Based on some optimal algorithms, large-size networks are aggregated to small-size ones. Then, by applying the principle minor theory to the small-size networks, a sufficient condition is given to reduce the number of controlled nodes. Finally, simulation results are given to illustrate the effectiveness of the developed criteria.</p>","PeriodicalId":13434,"journal":{"name":"IEEE transactions on neural networks","volume":"22 8","pages":"1231-40"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TNN.2011.2157938","citationCount":"40","resultStr":"{\"title\":\"Consensus analysis of multiagent networks via aggregated and pinning approaches.\",\"authors\":\"Wenjun Xiong, Daniel W C Ho, Zidong Wang\",\"doi\":\"10.1109/TNN.2011.2157938\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In this paper, the consensus problem of multiagent nonlinear directed networks (MNDNs) is discussed in the case that a MNDN does not have a spanning tree to reach the consensus of all nodes. By using the Lie algebra theory, a linear node-and-node pinning method is proposed to achieve a consensus of a MNDN for all nonlinear functions satisfying a given set of conditions. Based on some optimal algorithms, large-size networks are aggregated to small-size ones. Then, by applying the principle minor theory to the small-size networks, a sufficient condition is given to reduce the number of controlled nodes. Finally, simulation results are given to illustrate the effectiveness of the developed criteria.</p>\",\"PeriodicalId\":13434,\"journal\":{\"name\":\"IEEE transactions on neural networks\",\"volume\":\"22 8\",\"pages\":\"1231-40\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/TNN.2011.2157938\",\"citationCount\":\"40\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE transactions on neural networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TNN.2011.2157938\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2011/6/30 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE transactions on neural networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TNN.2011.2157938","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2011/6/30 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Consensus analysis of multiagent networks via aggregated and pinning approaches.
In this paper, the consensus problem of multiagent nonlinear directed networks (MNDNs) is discussed in the case that a MNDN does not have a spanning tree to reach the consensus of all nodes. By using the Lie algebra theory, a linear node-and-node pinning method is proposed to achieve a consensus of a MNDN for all nonlinear functions satisfying a given set of conditions. Based on some optimal algorithms, large-size networks are aggregated to small-size ones. Then, by applying the principle minor theory to the small-size networks, a sufficient condition is given to reduce the number of controlled nodes. Finally, simulation results are given to illustrate the effectiveness of the developed criteria.