{"title":"一类人在圈多代理系统的分布式编队控制","authors":"Xiao-Xiao Zhang;Huai-Ning Wu;Jin-Liang Wang","doi":"10.1109/THMS.2024.3398631","DOIUrl":null,"url":null,"abstract":"In this article, the distributed formation control problem for a class of human-in-the-loop (HiTL) multiagent systems (MASs) is studied. A hidden Markov jump MAS is employed to model the HiTL MAS, which integrates the human models, the MAS model, and their interactions. The HiTL MAS investigated in this article is composed of two parts: a leader without human in the control loop and a group of followers in which each follower is simultaneously controlled by a human operator and an automation. For each follower, a hidden Markov model is used for modeling the human behaviors in consideration of the random nature of human internal state (HIS) reasoning and the uncertainty from HIS observation. By means of a stochastic Lyapunov function, a necessary and sufficient condition is first developed in terms of the linear matrix inequalities (LMIs) to ensure the formation of the HiTL MAS in the mean-square sense. Then, an LMI approach to the human-assistance control design is proposed for the automations in the followers to guarantee the mean-square formation of the HiTL MAS. Finally, simulation results are presented to verify the effectiveness of the proposed methods.","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Distributed Formation Control for a Class of Human-in-the-Loop Multiagent Systems\",\"authors\":\"Xiao-Xiao Zhang;Huai-Ning Wu;Jin-Liang Wang\",\"doi\":\"10.1109/THMS.2024.3398631\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article, the distributed formation control problem for a class of human-in-the-loop (HiTL) multiagent systems (MASs) is studied. A hidden Markov jump MAS is employed to model the HiTL MAS, which integrates the human models, the MAS model, and their interactions. The HiTL MAS investigated in this article is composed of two parts: a leader without human in the control loop and a group of followers in which each follower is simultaneously controlled by a human operator and an automation. For each follower, a hidden Markov model is used for modeling the human behaviors in consideration of the random nature of human internal state (HIS) reasoning and the uncertainty from HIS observation. By means of a stochastic Lyapunov function, a necessary and sufficient condition is first developed in terms of the linear matrix inequalities (LMIs) to ensure the formation of the HiTL MAS in the mean-square sense. Then, an LMI approach to the human-assistance control design is proposed for the automations in the followers to guarantee the mean-square formation of the HiTL MAS. Finally, simulation results are presented to verify the effectiveness of the proposed methods.\",\"PeriodicalId\":48916,\"journal\":{\"name\":\"IEEE Transactions on Human-Machine Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Human-Machine Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10559606/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Human-Machine Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10559606/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
摘要
本文研究了一类人在回路(HiTL)多代理系统(MAS)的分布式编队控制问题。本文采用隐马尔可夫跃迁 MAS 对 HiTL MAS 进行建模,该模型集成了人类模型、MAS 模型以及它们之间的相互作用。本文研究的 HiTL MAS 由两部分组成:一个在控制环中没有人类的领导者和一组追随者,其中每个追随者同时受人类操作员和自动化设备的控制。考虑到人类内部状态(HIS)推理的随机性和 HIS 观察的不确定性,本文采用隐马尔可夫模型为每个追随者的人类行为建模。通过随机 Lyapunov 函数,首先从线性矩阵不等式(LMI)的角度提出了一个必要条件和充分条件,以确保在均方意义上形成 HiTL MAS。然后,为保证 HiTL MAS 的均方形成,对跟随者中的自动装置提出了一种线性矩阵不等式的人工辅助控制设计方法。最后,介绍了仿真结果,以验证所提方法的有效性。
Distributed Formation Control for a Class of Human-in-the-Loop Multiagent Systems
In this article, the distributed formation control problem for a class of human-in-the-loop (HiTL) multiagent systems (MASs) is studied. A hidden Markov jump MAS is employed to model the HiTL MAS, which integrates the human models, the MAS model, and their interactions. The HiTL MAS investigated in this article is composed of two parts: a leader without human in the control loop and a group of followers in which each follower is simultaneously controlled by a human operator and an automation. For each follower, a hidden Markov model is used for modeling the human behaviors in consideration of the random nature of human internal state (HIS) reasoning and the uncertainty from HIS observation. By means of a stochastic Lyapunov function, a necessary and sufficient condition is first developed in terms of the linear matrix inequalities (LMIs) to ensure the formation of the HiTL MAS in the mean-square sense. Then, an LMI approach to the human-assistance control design is proposed for the automations in the followers to guarantee the mean-square formation of the HiTL MAS. Finally, simulation results are presented to verify the effectiveness of the proposed methods.
期刊介绍:
The scope of the IEEE Transactions on Human-Machine Systems includes the fields of human machine systems. It covers human systems and human organizational interactions including cognitive ergonomics, system test and evaluation, and human information processing concerns in systems and organizations.