Identification of linear parameter-varying system with missing measurement data and outliers

被引：0

作者：

Chen, Xiang ^{[1
]}

Wang, Xiaogang ^{[1
]}

Liu, Fei ^{[1
]}

机构：

[1] Jiangnan Univ, Key Lab Adv Proc Control Light Ind, Minist Educ, Wuxi 214122, Peoples R China

来源：

JOURNAL OF THE FRANKLIN INSTITUTE | 2025年 / 362卷 / 04期

关键词：

LPV system; Student's t distribution; Unknown missing measurement; Variational Bayesian; Parameter identification; VARIATIONAL BAYESIAN-APPROACH; TIME-DELAY SYSTEM; HAMMERSTEIN MODELS; INFERENCE; NOISE;

D O I：

10.1016/j.jfranklin.2025.107547

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The robust identification of linear parameter-varying (LPV) finite impulse response (FIR) system with unknown missing output is considered. This paper provides a comprehensive discussion of common outliers and unknown missing measurement problems in practical processes. A Student's t distribution is utilized to data with outliers, and also to automatically identify missing measurements, an indicator variable is introduced for each measurement that follows a Bernoulli distribution. After that, determining whether measurements are missing or not and estimating the unknown parameters by the variational Bayesian (VB) algorithm. A numerical example and the cascaded tank system are provided to exemplify this algorithm and demonstrate its robustness and innovation.

引用

页数：14

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