Neural networks for system identification of coupled ship dynamics

P. Martin; Reza Katebi; I. Yamamoto; K. Daigo; E. Kobayashi; M. Matsuura; M. Hashimoto; H. Hirayama; N. Okamoto

Neural networks for system identification of coupled ship dynamics

P. Martin, Reza Katebi, I. Yamamoto, K. Daigo, E. Kobayashi, M. Matsuura, M. Hashimoto, H. Hirayama, N. Okamoto

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

Abstract

System identification of coupled ship dynamics is problematic with standard least squares methods due to the non-linear, multivariable nature of the system. Neural Networks have therefore been applied to this problem, as they are particularly suitable for approximating non-linear, multivariable functions. In this paper, results of identification with Neural Networks are given for a ship motion simulation based on a standard mathematical model, and for real data collected from a 1/50(th) scale model of the system. The method is seen to be successful at various operating points, and ideas for extension of the work are discussed.

Original language	English
Title of host publication	Control applications in marine systems 2001 (CAMS 2001)
Subtitle of host publication	proceedings of IFAC conference on control applications in marine systems
Editors	R. Katebi
Place of Publication	Kidlington
Pages	83-88
Number of pages	6
Publication status	Published - 2002
Event	IFAC Conference on Control Applications in Marine Systems - Glasgow, United Kingdom Duration: 18 Jul 2001 → 20 Jul 2001

Publication series

Name	IFAC Proceedings Series
Publisher	Pergamon-Elsevier

Conference

Conference	IFAC Conference on Control Applications in Marine Systems
Country/Territory	United Kingdom
City	Glasgow
Period	18/07/01 → 20/07/01

Keywords

neural networks
system identification
coupled ship dynamics

Cite this

Martin, P., Katebi, R., Yamamoto, I., Daigo, K., Kobayashi, E., Matsuura, M., Hashimoto, M., Hirayama, H., & Okamoto, N. (2002). Neural networks for system identification of coupled ship dynamics. In R. Katebi (Ed.), Control applications in marine systems 2001 (CAMS 2001) : proceedings of IFAC conference on control applications in marine systems (pp. 83-88). (IFAC Proceedings Series)..

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title = "Neural networks for system identification of coupled ship dynamics",

abstract = "System identification of coupled ship dynamics is problematic with standard least squares methods due to the non-linear, multivariable nature of the system. Neural Networks have therefore been applied to this problem, as they are particularly suitable for approximating non-linear, multivariable functions. In this paper, results of identification with Neural Networks are given for a ship motion simulation based on a standard mathematical model, and for real data collected from a 1/50(th) scale model of the system. The method is seen to be successful at various operating points, and ideas for extension of the work are discussed. ",

keywords = "neural networks, system identification, coupled ship dynamics",

author = "P. Martin and Reza Katebi and I. Yamamoto and K. Daigo and E. Kobayashi and M. Matsuura and M. Hashimoto and H. Hirayama and N. Okamoto",

year = "2002",

language = "English",

isbn = "0080432360 ",

series = "IFAC Proceedings Series",

publisher = "Pergamon-Elsevier",

pages = "83--88",

editor = "R. Katebi",

booktitle = "Control applications in marine systems 2001 (CAMS 2001)",

note = "IFAC Conference on Control Applications in Marine Systems ; Conference date: 18-07-2001 Through 20-07-2001",

}

Martin, P, Katebi, R, Yamamoto, I, Daigo, K, Kobayashi, E, Matsuura, M, Hashimoto, M, Hirayama, H & Okamoto, N 2002, Neural networks for system identification of coupled ship dynamics. in R Katebi (ed.), Control applications in marine systems 2001 (CAMS 2001) : proceedings of IFAC conference on control applications in marine systems . IFAC Proceedings Series, Kidlington, pp. 83-88, IFAC Conference on Control Applications in Marine Systems , Glasgow, United Kingdom, 18/07/01.

Neural networks for system identification of coupled ship dynamics. / Martin, P.; Katebi, Reza; Yamamoto, I. et al.
Control applications in marine systems 2001 (CAMS 2001) : proceedings of IFAC conference on control applications in marine systems . ed. / R. Katebi. Kidlington, 2002. p. 83-88 (IFAC Proceedings Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

TY - GEN

T1 - Neural networks for system identification of coupled ship dynamics

AU - Martin, P.

AU - Katebi, Reza

AU - Yamamoto, I.

AU - Daigo, K.

AU - Kobayashi, E.

AU - Matsuura, M.

AU - Hashimoto, M.

AU - Hirayama, H.

AU - Okamoto, N.

PY - 2002

Y1 - 2002

N2 - System identification of coupled ship dynamics is problematic with standard least squares methods due to the non-linear, multivariable nature of the system. Neural Networks have therefore been applied to this problem, as they are particularly suitable for approximating non-linear, multivariable functions. In this paper, results of identification with Neural Networks are given for a ship motion simulation based on a standard mathematical model, and for real data collected from a 1/50(th) scale model of the system. The method is seen to be successful at various operating points, and ideas for extension of the work are discussed.

AB - System identification of coupled ship dynamics is problematic with standard least squares methods due to the non-linear, multivariable nature of the system. Neural Networks have therefore been applied to this problem, as they are particularly suitable for approximating non-linear, multivariable functions. In this paper, results of identification with Neural Networks are given for a ship motion simulation based on a standard mathematical model, and for real data collected from a 1/50(th) scale model of the system. The method is seen to be successful at various operating points, and ideas for extension of the work are discussed.

KW - neural networks

KW - system identification

KW - coupled ship dynamics

M3 - Conference contribution book

SN - 0080432360

T3 - IFAC Proceedings Series

SP - 83

EP - 88

BT - Control applications in marine systems 2001 (CAMS 2001)

A2 - Katebi, R.

CY - Kidlington

T2 - IFAC Conference on Control Applications in Marine Systems

Y2 - 18 July 2001 through 20 July 2001

ER -

Neural networks for system identification of coupled ship dynamics

Abstract

Publication series

Conference

Keywords

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