Real-Time Optimal State Estimation of Multi-DOF Industrial Systems Using FIR Filtering

Shunyi Zhao; Yuriy S. Shmaliy; Choon Ki Ahn; Peng Shi

doi:10.1109/TII.2016.2601071

Real-Time Optimal State Estimation of Multi-DOF Industrial Systems Using FIR Filtering

Shunyi Zhao, Yuriy S. Shmaliy, Choon Ki Ahn, Peng Shi

Research output: Contribution to journal › Article › peer-review

26 Citations (Scopus)

Abstract

Industrial processes are often organized using mechanical systems with multiple degrees-of-freedom (DOF). For real-time operation of such systems in noise environments, fast, optimal, and robust estimators are required. In this paper, information gathering about multi-DOF system states is provided using the optimal finite impulse response (OFIR) filter. To use this filter in real time, a fast iterative algorithm is developed with a pseudocode available for immediate use. Although the iterative algorithm utilizes Kalman recursions, it is more robust against uncertainties and model errors owing to the transversal structure. We use this algorithm to estimate state in the 1-DOF torsion system and the 3-DOF helicopter system.

Original language	English
Article number	7546834
Pages (from-to)	967-975
Number of pages	9
Journal	IEEE Transactions on Industrial Informatics
Volume	13
Issue number	3
DOIs	https://doi.org/10.1109/TII.2016.2601071
Publication status	Published - 2017 Jun

Keywords

Automation process
Kalman filter (KF)
finite impulse response (FIR) filter
iterative algorithm
state estimation
time-variant system

ASJC Scopus subject areas

Control and Systems Engineering
Information Systems
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TII.2016.2601071

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@article{c38256e99f914a0badd36054c808ff80,

title = "Real-Time Optimal State Estimation of Multi-DOF Industrial Systems Using FIR Filtering",

abstract = "Industrial processes are often organized using mechanical systems with multiple degrees-of-freedom (DOF). For real-time operation of such systems in noise environments, fast, optimal, and robust estimators are required. In this paper, information gathering about multi-DOF system states is provided using the optimal finite impulse response (OFIR) filter. To use this filter in real time, a fast iterative algorithm is developed with a pseudocode available for immediate use. Although the iterative algorithm utilizes Kalman recursions, it is more robust against uncertainties and model errors owing to the transversal structure. We use this algorithm to estimate state in the 1-DOF torsion system and the 3-DOF helicopter system.",

keywords = "Automation process, Kalman filter (KF), finite impulse response (FIR) filter, iterative algorithm, state estimation, time-variant system",

author = "Shunyi Zhao and Shmaliy, {Yuriy S.} and Ahn, {Choon Ki} and Peng Shi",

note = "Funding Information: This work was supported in part by the National Natural Science Foundation of China under Grants 61603155, 61573112 and U1509217, in part by the Australian Research Council under Grant DP140102180 and Grant LP140100471, in part by the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2014R1A1A1006101), and in part by the 111 Project (B12018) Publisher Copyright: {\textcopyright} 2016 IEEE.",

year = "2017",

month = jun,

doi = "10.1109/TII.2016.2601071",

language = "English",

volume = "13",

pages = "967--975",

journal = "IEEE Transactions on Industrial Informatics",

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publisher = "IEEE Computer Society",

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AU - Zhao, Shunyi

AU - Shmaliy, Yuriy S.

AU - Ahn, Choon Ki

AU - Shi, Peng

N1 - Funding Information: This work was supported in part by the National Natural Science Foundation of China under Grants 61603155, 61573112 and U1509217, in part by the Australian Research Council under Grant DP140102180 and Grant LP140100471, in part by the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2014R1A1A1006101), and in part by the 111 Project (B12018) Publisher Copyright: © 2016 IEEE.

PY - 2017/6

Y1 - 2017/6

N2 - Industrial processes are often organized using mechanical systems with multiple degrees-of-freedom (DOF). For real-time operation of such systems in noise environments, fast, optimal, and robust estimators are required. In this paper, information gathering about multi-DOF system states is provided using the optimal finite impulse response (OFIR) filter. To use this filter in real time, a fast iterative algorithm is developed with a pseudocode available for immediate use. Although the iterative algorithm utilizes Kalman recursions, it is more robust against uncertainties and model errors owing to the transversal structure. We use this algorithm to estimate state in the 1-DOF torsion system and the 3-DOF helicopter system.

AB - Industrial processes are often organized using mechanical systems with multiple degrees-of-freedom (DOF). For real-time operation of such systems in noise environments, fast, optimal, and robust estimators are required. In this paper, information gathering about multi-DOF system states is provided using the optimal finite impulse response (OFIR) filter. To use this filter in real time, a fast iterative algorithm is developed with a pseudocode available for immediate use. Although the iterative algorithm utilizes Kalman recursions, it is more robust against uncertainties and model errors owing to the transversal structure. We use this algorithm to estimate state in the 1-DOF torsion system and the 3-DOF helicopter system.

KW - Automation process

KW - Kalman filter (KF)

KW - finite impulse response (FIR) filter

KW - iterative algorithm

KW - state estimation

KW - time-variant system

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U2 - 10.1109/TII.2016.2601071

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JO - IEEE Transactions on Industrial Informatics

JF - IEEE Transactions on Industrial Informatics

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ER -

Real-Time Optimal State Estimation of Multi-DOF Industrial Systems Using FIR Filtering

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Keywords

ASJC Scopus subject areas

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