{"title":"不稳定性在互联网络中的传播","authors":"Amy Koh, G. Vinnicombe","doi":"10.1109/CDC.2012.6426636","DOIUrl":null,"url":null,"abstract":"We consider how instability, when due to local interactions between agents in one part of a network, affects other parts of the network. In this initial work, we consider a stable bipartite system with homogeneous linear dynamics in each partition. The initially stable system is driven to the onset of instability by a local gain perturbation and we define a measure which indicates how the size of the resulting oscillations decays with nodal distance. For interconnections defined on d =1;2 dimensional lattices, we determine the asymptotic value of this measure, as the size of the network increases, using a Markov chain framework. In addition, approximate results are given for interconnection topologies described by a classical random graph model.","PeriodicalId":312426,"journal":{"name":"2012 IEEE 51st IEEE Conference on Decision and Control (CDC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"On the propagation of instability in interconnected networks\",\"authors\":\"Amy Koh, G. Vinnicombe\",\"doi\":\"10.1109/CDC.2012.6426636\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider how instability, when due to local interactions between agents in one part of a network, affects other parts of the network. In this initial work, we consider a stable bipartite system with homogeneous linear dynamics in each partition. The initially stable system is driven to the onset of instability by a local gain perturbation and we define a measure which indicates how the size of the resulting oscillations decays with nodal distance. For interconnections defined on d =1;2 dimensional lattices, we determine the asymptotic value of this measure, as the size of the network increases, using a Markov chain framework. In addition, approximate results are given for interconnection topologies described by a classical random graph model.\",\"PeriodicalId\":312426,\"journal\":{\"name\":\"2012 IEEE 51st IEEE Conference on Decision and Control (CDC)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE 51st IEEE Conference on Decision and Control (CDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.2012.6426636\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 51st IEEE Conference on Decision and Control (CDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.2012.6426636","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the propagation of instability in interconnected networks
We consider how instability, when due to local interactions between agents in one part of a network, affects other parts of the network. In this initial work, we consider a stable bipartite system with homogeneous linear dynamics in each partition. The initially stable system is driven to the onset of instability by a local gain perturbation and we define a measure which indicates how the size of the resulting oscillations decays with nodal distance. For interconnections defined on d =1;2 dimensional lattices, we determine the asymptotic value of this measure, as the size of the network increases, using a Markov chain framework. In addition, approximate results are given for interconnection topologies described by a classical random graph model.