Estimation of Hydrodynamic Coefficients using Unscented Kalman Filter and Recursive Least Square

Subchan Subchan; Rachmat Wahyudi Ismail; Tahiyatul Asfihani; Dieky Adzkiya

doi:10.1109/IWCIA47330.2019.8955002

Estimation of Hydrodynamic Coefficients using Unscented Kalman Filter and Recursive Least Square

Subchan Subchan, Rachmat Wahyudi Ismail, Tahiyatul Asfihani, Dieky Adzkiya

Institut Teknologi Sepuluh Nopember

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

Ship maneuvering is the ability of ships to turn and spin while operating on seas. The ship's hydrodynamic coefficients are a set of parameters that influence the mathematical model of ship motion. In other words, if the hydrodynamic coefficients are more accurate, the ship motion produced by the model is closer to the actual motion. This study uses unscented Kalman filter and recursive least square to estimate the hydrodynamic coefficients in the 4-DOF ship motion models based on the data from free running model test.

Original language	English
Title of host publication	2019 IEEE 11th International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	9-13
Number of pages	5
ISBN (Electronic)	9781728124292
DOIs	https://doi.org/10.1109/IWCIA47330.2019.8955002
Publication status	Published - Nov 2019
Event	11th IEEE International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Hiroshima, Japan Duration: 9 Nov 2019 → 10 Nov 2019

Publication series

Name	2019 IEEE 11th International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Proceedings

Conference

Conference	11th IEEE International Workshop on Computational Intelligence and Applications, IWCIA 2019
Country/Territory	Japan
City	Hiroshima
Period	9/11/19 → 10/11/19

Keywords

free running model test
hydrodynamic coefficients
recursive least square
unscented Kalman filter

Access to Document

10.1109/IWCIA47330.2019.8955002

Cite this

Subchan, S., Ismail, R. W., Asfihani, T., & Adzkiya, D. (2019). Estimation of Hydrodynamic Coefficients using Unscented Kalman Filter and Recursive Least Square. In 2019 IEEE 11th International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Proceedings (pp. 9-13). Article 8955002 (2019 IEEE 11th International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWCIA47330.2019.8955002

Subchan, Subchan ; Ismail, Rachmat Wahyudi ; Asfihani, Tahiyatul et al. / Estimation of Hydrodynamic Coefficients using Unscented Kalman Filter and Recursive Least Square. 2019 IEEE 11th International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 9-13 (2019 IEEE 11th International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Proceedings).

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title = "Estimation of Hydrodynamic Coefficients using Unscented Kalman Filter and Recursive Least Square",

abstract = "Ship maneuvering is the ability of ships to turn and spin while operating on seas. The ship's hydrodynamic coefficients are a set of parameters that influence the mathematical model of ship motion. In other words, if the hydrodynamic coefficients are more accurate, the ship motion produced by the model is closer to the actual motion. This study uses unscented Kalman filter and recursive least square to estimate the hydrodynamic coefficients in the 4-DOF ship motion models based on the data from free running model test.",

keywords = "free running model test, hydrodynamic coefficients, recursive least square, unscented Kalman filter",

author = "Subchan Subchan and Ismail, {Rachmat Wahyudi} and Tahiyatul Asfihani and Dieky Adzkiya",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 11th IEEE International Workshop on Computational Intelligence and Applications, IWCIA 2019 ; Conference date: 09-11-2019 Through 10-11-2019",

year = "2019",

month = nov,

doi = "10.1109/IWCIA47330.2019.8955002",

language = "English",

series = "2019 IEEE 11th International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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address = "United States",

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Subchan, S, Ismail, RW, Asfihani, T & Adzkiya, D 2019, Estimation of Hydrodynamic Coefficients using Unscented Kalman Filter and Recursive Least Square. in 2019 IEEE 11th International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Proceedings., 8955002, 2019 IEEE 11th International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 9-13, 11th IEEE International Workshop on Computational Intelligence and Applications, IWCIA 2019, Hiroshima, Japan, 9/11/19. https://doi.org/10.1109/IWCIA47330.2019.8955002

Estimation of Hydrodynamic Coefficients using Unscented Kalman Filter and Recursive Least Square. / Subchan, Subchan; Ismail, Rachmat Wahyudi; Asfihani, Tahiyatul et al.
2019 IEEE 11th International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. p. 9-13 8955002 (2019 IEEE 11th International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Adzkiya, Dieky

PY - 2019/11

Y1 - 2019/11

N2 - Ship maneuvering is the ability of ships to turn and spin while operating on seas. The ship's hydrodynamic coefficients are a set of parameters that influence the mathematical model of ship motion. In other words, if the hydrodynamic coefficients are more accurate, the ship motion produced by the model is closer to the actual motion. This study uses unscented Kalman filter and recursive least square to estimate the hydrodynamic coefficients in the 4-DOF ship motion models based on the data from free running model test.

AB - Ship maneuvering is the ability of ships to turn and spin while operating on seas. The ship's hydrodynamic coefficients are a set of parameters that influence the mathematical model of ship motion. In other words, if the hydrodynamic coefficients are more accurate, the ship motion produced by the model is closer to the actual motion. This study uses unscented Kalman filter and recursive least square to estimate the hydrodynamic coefficients in the 4-DOF ship motion models based on the data from free running model test.

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M3 - Conference contribution

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BT - 2019 IEEE 11th International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Proceedings

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Subchan S, Ismail RW, Asfihani T , Adzkiya D. Estimation of Hydrodynamic Coefficients using Unscented Kalman Filter and Recursive Least Square. In 2019 IEEE 11th International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. p. 9-13. 8955002. (2019 IEEE 11th International Workshop on Computational Intelligence and Applications, IWCIA 2019 - Proceedings). doi: 10.1109/IWCIA47330.2019.8955002

Estimation of Hydrodynamic Coefficients using Unscented Kalman Filter and Recursive Least Square

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