{"title":"利用位移测量进行联合估计和平面仿射编队控制","authors":"Qingkai Yang;Xiaozhen Zhang;Hao Fang;Ming Cao;Jie Chen","doi":"10.1109/TCST.2024.3449008","DOIUrl":null,"url":null,"abstract":"This article investigates the problem of planar affine formation maneuver control with a matrix-valued formation shape variation parameter. The matrix representation renders full degree of freedom (DOF) motion associated with linear mappings in the context of affine transformation. Unlike the typical leader–follower setup, where all the leaders know the prescribed formation information, only a portion of leaders are informed of the matrix parameter in this article. To achieve affine formation stabilization, two types of distributed estimators are developed for the remaining leaders to infer constant and dynamic matrix parameters, utilizing only local displacement measurements. Then, we establish a joint estimation and cooperative control framework, generating corresponding formation shape changes in consistent with the matrix parameter. The system stability and precise estimation convergence are verified via both rigorous theoretical analyses and simulations with large-scale swarms. Finally, experiments conducted on the Crazyflie robots also validate the effectiveness and practicality of the proposed control approach.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"92-105"},"PeriodicalIF":4.9000,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Joint Estimation and Planar Affine Formation Control With Displacement Measurements\",\"authors\":\"Qingkai Yang;Xiaozhen Zhang;Hao Fang;Ming Cao;Jie Chen\",\"doi\":\"10.1109/TCST.2024.3449008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article investigates the problem of planar affine formation maneuver control with a matrix-valued formation shape variation parameter. The matrix representation renders full degree of freedom (DOF) motion associated with linear mappings in the context of affine transformation. Unlike the typical leader–follower setup, where all the leaders know the prescribed formation information, only a portion of leaders are informed of the matrix parameter in this article. To achieve affine formation stabilization, two types of distributed estimators are developed for the remaining leaders to infer constant and dynamic matrix parameters, utilizing only local displacement measurements. Then, we establish a joint estimation and cooperative control framework, generating corresponding formation shape changes in consistent with the matrix parameter. The system stability and precise estimation convergence are verified via both rigorous theoretical analyses and simulations with large-scale swarms. Finally, experiments conducted on the Crazyflie robots also validate the effectiveness and practicality of the proposed control approach.\",\"PeriodicalId\":13103,\"journal\":{\"name\":\"IEEE Transactions on Control Systems Technology\",\"volume\":\"33 1\",\"pages\":\"92-105\"},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2024-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Control Systems Technology\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10665928/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Control Systems Technology","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10665928/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Joint Estimation and Planar Affine Formation Control With Displacement Measurements
This article investigates the problem of planar affine formation maneuver control with a matrix-valued formation shape variation parameter. The matrix representation renders full degree of freedom (DOF) motion associated with linear mappings in the context of affine transformation. Unlike the typical leader–follower setup, where all the leaders know the prescribed formation information, only a portion of leaders are informed of the matrix parameter in this article. To achieve affine formation stabilization, two types of distributed estimators are developed for the remaining leaders to infer constant and dynamic matrix parameters, utilizing only local displacement measurements. Then, we establish a joint estimation and cooperative control framework, generating corresponding formation shape changes in consistent with the matrix parameter. The system stability and precise estimation convergence are verified via both rigorous theoretical analyses and simulations with large-scale swarms. Finally, experiments conducted on the Crazyflie robots also validate the effectiveness and practicality of the proposed control approach.
期刊介绍:
The IEEE Transactions on Control Systems Technology publishes high quality technical papers on technological advances in control engineering. The word technology is from the Greek technologia. The modern meaning is a scientific method to achieve a practical purpose. Control Systems Technology includes all aspects of control engineering needed to implement practical control systems, from analysis and design, through simulation and hardware. A primary purpose of the IEEE Transactions on Control Systems Technology is to have an archival publication which will bridge the gap between theory and practice. Papers are published in the IEEE Transactions on Control System Technology which disclose significant new knowledge, exploratory developments, or practical applications in all aspects of technology needed to implement control systems, from analysis and design through simulation, and hardware.