{"title":"Formation Tracking Control Design for Uncertain Artificial Swarm Systems","authors":"Jiale Zhang, R. Zhao, Shengjie Jiao, Yapeng Wang","doi":"10.1109/ICMEE56406.2022.10093431","DOIUrl":null,"url":null,"abstract":"A novel formation tracking control approach for uncertain artificial swarm systems is designed. In this paper, agents can not only track fixed targets but also perform swarm behaviors, and the swarm behaviors are regarded as control targets for the agent. By the Udwadia-Kalaba theory, dynamic control is presented for each agent to ensure that the artificial swarm systems meet the required movement. Additionally, the uncertainties of the agents, which is unknown and time-varying (but bound), are considered. To estimate boundary information, a new adaptive law is designed. The artificial swarm systems' performances under the designed method are guaranteed by Lyapunov stability and numerical verification by simulation.","PeriodicalId":333538,"journal":{"name":"2022 International Conference on Mechanical and Electronics Engineering (ICMEE)","volume":"184 12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Mechanical and Electronics Engineering (ICMEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMEE56406.2022.10093431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
A novel formation tracking control approach for uncertain artificial swarm systems is designed. In this paper, agents can not only track fixed targets but also perform swarm behaviors, and the swarm behaviors are regarded as control targets for the agent. By the Udwadia-Kalaba theory, dynamic control is presented for each agent to ensure that the artificial swarm systems meet the required movement. Additionally, the uncertainties of the agents, which is unknown and time-varying (but bound), are considered. To estimate boundary information, a new adaptive law is designed. The artificial swarm systems' performances under the designed method are guaranteed by Lyapunov stability and numerical verification by simulation.