文章基本信息

标题：Approximated unbiased minimum-variance simultaneous states and parameters estimation for nonlinear systems
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作者：Shinji Ishihara ; Masaki Yamakita
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：1607-1612
DOI：10.1016/j.ifacol.2017.08.318
语种：English
出版社：Elsevier
摘要：AbstractThis paper addresses joint state and parameter estimation problem for nonlinear systems. We linearize the nonlinear system by unscented statistical linearization (USL) and decouple unknown parameter vector of state vector. Then, we treat unknown parameter vector as unknown inputs to the approximated linear model. Furthermore, we applied unbiased minimum variance estimation (UMVE) method for the approximated linear system with unknown input. Our proposed method also offers an easy way to apply the UMVE to nonlinear systems. We confirm the validity of the proposed methods by Monte Carlo simulations.
关键词：KeywordsNonlinear filtersParameter estimationState estimationNonlinear sysytemsUncertain dynamic systems