文章基本信息

标题：Minimum-variance unbiased unknown input and state estimation for multi-agent systems with direct feedthrough by using distributed cooperative filters
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作者：Changqing Liu ; Youqing Wang
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：24
页码：286-291
DOI：10.1016/j.ifacol.2018.09.590
语种：English
出版社：Elsevier
摘要：AbstractThis paper addresses the problem of simultaneous estimation of unknown inputs and states in multi-agent systems with direct feedthrough. A group of cooperative distributed recursive filters, in the sense of minimum-variance unbiased (MVU), is developed, where the estimations of the unknown input and state are interconnected. Theoretical and numerical analyses show that the existing condition of the proposed filters is significantly relaxed compared with that of the conventional decentralized filters.
关键词：KeywordsMVU estimationmulti-agent systemdirect feedthroughdistributed cooperative filters