Pitch-depth control of submarine operating in shallow water via neuro-adaptive approach

Y. D. SONG; Liguo WENG; Medorian D. GHEORGHIU

doi:10.1007/978-3-642-10690-3_8

Pitch-depth control of submarine operating in shallow water via neuro-adaptive approach

Y. D. SONG^*
, Liguo WENG
, Medorian D. GHEORGHIU

^*Corresponding author for this work

Research output: Book Chapters | Papers in Conference Proceedings › Book Chapter › Research › peer-review

Abstract

This chapter presented a neuro-adaptive control for depth and pitch control of submarine operating in shallow waters. The control scheme is based on two neural-network (NN) units which are shown to be effective in attenuating the reconstruction error and other lumped system uncertainties. Stable on-line weight-tuning algorithms are derived based on Lyapunov's stability theory. Variable heading speed and changing center of gravity are taken into consideration in control design. Theoretical analyses and simulations prove the efficacy of the proposed control scheme in dealing with external disturbances as well as system nonlinearities, uncertainties, and parameter variations. © 2010 Springer-Verlag Berlin Heidelberg.

Original language	English
Title of host publication	Applications of Neural Networks in High Assurance Systems
Editors	Johann SCHUAMANN, Yan LIU
Publisher	Springer Berlin Heidelberg
Pages	165-178
Number of pages	14
ISBN (Electronic)	9783642106903
ISBN (Print)	9783642106897
DOIs	https://doi.org/10.1007/978-3-642-10690-3_8
Publication status	Published - 2010
Externally published	Yes

Publication series

Name	Studies in Computational Intelligence
Publisher	Springer Berlin, Heidelberg
ISSN (Print)	1860-949X
ISSN (Electronic)	1860-9503

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10.1007/978-3-642-10690-3_8

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title = "Pitch-depth control of submarine operating in shallow water via neuro-adaptive approach",

abstract = "This chapter presented a neuro-adaptive control for depth and pitch control of submarine operating in shallow waters. The control scheme is based on two neural-network (NN) units which are shown to be effective in attenuating the reconstruction error and other lumped system uncertainties. Stable on-line weight-tuning algorithms are derived based on Lyapunov's stability theory. Variable heading speed and changing center of gravity are taken into consideration in control design. Theoretical analyses and simulations prove the efficacy of the proposed control scheme in dealing with external disturbances as well as system nonlinearities, uncertainties, and parameter variations. {\textcopyright} 2010 Springer-Verlag Berlin Heidelberg.",

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year = "2010",

doi = "10.1007/978-3-642-10690-3\_8",

language = "English",

isbn = "9783642106897",

series = "Studies in Computational Intelligence",

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booktitle = "Applications of Neural Networks in High Assurance Systems",

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Pitch-depth control of submarine operating in shallow water via neuro-adaptive approach. / SONG, Y. D.; WENG, Liguo; GHEORGHIU, Medorian D.
Applications of Neural Networks in High Assurance Systems. ed. / Johann SCHUAMANN; Yan LIU. Springer Berlin Heidelberg, 2010. p. 165-178 (Studies in Computational Intelligence).

Research output: Book Chapters | Papers in Conference Proceedings › Book Chapter › Research › peer-review

TY - CHAP

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AU - SONG, Y. D.

AU - WENG, Liguo

AU - GHEORGHIU, Medorian D.

PY - 2010

Y1 - 2010

N2 - This chapter presented a neuro-adaptive control for depth and pitch control of submarine operating in shallow waters. The control scheme is based on two neural-network (NN) units which are shown to be effective in attenuating the reconstruction error and other lumped system uncertainties. Stable on-line weight-tuning algorithms are derived based on Lyapunov's stability theory. Variable heading speed and changing center of gravity are taken into consideration in control design. Theoretical analyses and simulations prove the efficacy of the proposed control scheme in dealing with external disturbances as well as system nonlinearities, uncertainties, and parameter variations. © 2010 Springer-Verlag Berlin Heidelberg.

AB - This chapter presented a neuro-adaptive control for depth and pitch control of submarine operating in shallow waters. The control scheme is based on two neural-network (NN) units which are shown to be effective in attenuating the reconstruction error and other lumped system uncertainties. Stable on-line weight-tuning algorithms are derived based on Lyapunov's stability theory. Variable heading speed and changing center of gravity are taken into consideration in control design. Theoretical analyses and simulations prove the efficacy of the proposed control scheme in dealing with external disturbances as well as system nonlinearities, uncertainties, and parameter variations. © 2010 Springer-Verlag Berlin Heidelberg.

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BT - Applications of Neural Networks in High Assurance Systems

A2 - SCHUAMANN, Johann

A2 - LIU, Yan

PB - Springer Berlin Heidelberg

ER -

Pitch-depth control of submarine operating in shallow water via neuro-adaptive approach

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