{"title":"具有未知干扰的多个航天器系统的边缘触发式领导者-追随者共识","authors":"Dong Liang;Shimin Wang;Engang Tian","doi":"10.1109/TSIPN.2024.3467916","DOIUrl":null,"url":null,"abstract":"Multiple rigid bodies can model various practical industrial systems. However, periodic sampled-data communication can have a load over the network subject to limited bandwidth. The research on the leader-follower attitude consensus issue for a group of rigid-body dynamics is conducted in this technical paper. The plant of each follower is subject to unknown external disturbances. To reduce the burden of the communication network, an edge-triggered nonlinear distributed observer with dynamic triggering mechanisms is presented. The proposed observer has the ability to evaluate the leader system's state regardless of implementing the continuous-time exchange of the neighborhood information. The proposed edge-based triggering mechanism is asynchronous while eliminating the Zeno phenomenon. Based on the nonlinear observer, a distributed control protocol together with an adaptive law is put forward in order to realize the leader-follower attitude consensus while attenuating the unknown external disturbances. In the end, an illustrative example of a collection of spacecraft systems is provided to verify the feasibility of our methods.","PeriodicalId":56268,"journal":{"name":"IEEE Transactions on Signal and Information Processing over Networks","volume":"10 ","pages":"740-751"},"PeriodicalIF":3.0000,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Edge-Triggered Leader–Follower Consensus of Multiple Spacecraft Systems With Unknown Disturbances\",\"authors\":\"Dong Liang;Shimin Wang;Engang Tian\",\"doi\":\"10.1109/TSIPN.2024.3467916\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multiple rigid bodies can model various practical industrial systems. However, periodic sampled-data communication can have a load over the network subject to limited bandwidth. The research on the leader-follower attitude consensus issue for a group of rigid-body dynamics is conducted in this technical paper. The plant of each follower is subject to unknown external disturbances. To reduce the burden of the communication network, an edge-triggered nonlinear distributed observer with dynamic triggering mechanisms is presented. The proposed observer has the ability to evaluate the leader system's state regardless of implementing the continuous-time exchange of the neighborhood information. The proposed edge-based triggering mechanism is asynchronous while eliminating the Zeno phenomenon. Based on the nonlinear observer, a distributed control protocol together with an adaptive law is put forward in order to realize the leader-follower attitude consensus while attenuating the unknown external disturbances. In the end, an illustrative example of a collection of spacecraft systems is provided to verify the feasibility of our methods.\",\"PeriodicalId\":56268,\"journal\":{\"name\":\"IEEE Transactions on Signal and Information Processing over Networks\",\"volume\":\"10 \",\"pages\":\"740-751\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Signal and Information Processing over Networks\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10694715/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Signal and Information Processing over Networks","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10694715/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Edge-Triggered Leader–Follower Consensus of Multiple Spacecraft Systems With Unknown Disturbances
Multiple rigid bodies can model various practical industrial systems. However, periodic sampled-data communication can have a load over the network subject to limited bandwidth. The research on the leader-follower attitude consensus issue for a group of rigid-body dynamics is conducted in this technical paper. The plant of each follower is subject to unknown external disturbances. To reduce the burden of the communication network, an edge-triggered nonlinear distributed observer with dynamic triggering mechanisms is presented. The proposed observer has the ability to evaluate the leader system's state regardless of implementing the continuous-time exchange of the neighborhood information. The proposed edge-based triggering mechanism is asynchronous while eliminating the Zeno phenomenon. Based on the nonlinear observer, a distributed control protocol together with an adaptive law is put forward in order to realize the leader-follower attitude consensus while attenuating the unknown external disturbances. In the end, an illustrative example of a collection of spacecraft systems is provided to verify the feasibility of our methods.
期刊介绍:
The IEEE Transactions on Signal and Information Processing over Networks publishes high-quality papers that extend the classical notions of processing of signals defined over vector spaces (e.g. time and space) to processing of signals and information (data) defined over networks, potentially dynamically varying. In signal processing over networks, the topology of the network may define structural relationships in the data, or may constrain processing of the data. Topics include distributed algorithms for filtering, detection, estimation, adaptation and learning, model selection, data fusion, and diffusion or evolution of information over such networks, and applications of distributed signal processing.