文章基本信息

标题：Robust Identification of Switching Markov ARX Models Using EM Algorithm * * This work is supported in part by NSERC and AITF.
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作者：Lei Fan ; Hariprasad Kodamana ; Biao Huang 等
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：9772-9777
DOI：10.1016/j.ifacol.2017.08.878
语种：English
出版社：Elsevier
摘要：AbstractOutliers are one of the common factors that affect the quality of routine operational data. In this work, we propose a robust identification approach for the Switched Markov Autoregressive eXogeneous (SMARX) system to deal with outliers. The robust identification problem is formulated by imposing Student’s t-distribution to the noise model. The Expectation-Maximization algorithm is adopted to estimate the parameters of both the continuous dynamics described by local ARX models and discrete dynamics described by Hidden Markov Model. The advantages of the proposed approach are demonstrated through a numerical simulation.
关键词：KeywordsHybridswitched systems modelingLPV systemsNonlinear system identificationHMMEM algorithmt-distribution