Online state and inputs identification for stochastic systems using recursive expectation-maximization algorithm-Reference-Cited by-同舟云学术

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Online state and inputs identification for stochastic systems using recursive expectation-maximization algorithm

Published:2021-10 Issue: Volume:217 Page:104403
ISSN:0169-7439
Container-title:Chemometrics and Intelligent Laboratory Systems
language:en
Short-container-title:Chemometrics and Intelligent Laboratory Systems

Author:

Liu Zhuangyu,Zhao Shunyi,Luan Xiaoli,Liu Fei

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Spectroscopy,Process Chemistry and Technology,Computer Science Applications,Software,Analytical Chemistry

Reference37 articles.

1. State estimation and unknown input reconstruction via both reduced-order and high-order sliding mode observers;Zhu;J. Process Contr.,2012

2. Unbiased minimum-variance state estimation for linear systems with unknown input;Cheng;Automatica,2009

3. State estimation for descriptor systems via the unknown input filtering method;Hsieh;Automatica,2013

4. Robust estimation and fault detection and isolation algorithms for stochastic linear hybrid systems with unknown fault input;Liu;IET Control Theory & Appl.,2011

5. Framework for state and unknown input estimation of linear time-varying systems;Lu;Automatica,2016

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Joint state and process inputs estimation for state-space models with Student’s t-distribution;Chemometrics and Intelligent Laboratory Systems;2024-10

2. Online state and unknown inputs estimation for nonlinear systems with particle filter based recursive expectation‐maximization algorithm;International Journal of Robust and Nonlinear Control;2024-05-28

3. Improved state estimator for linear-Gaussian systems subject to initialization errors;Chemometrics and Intelligent Laboratory Systems;2022-08

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