Control of submarine operating in shallow waters: A neuro-adaptive based approach

Medorian D. GHEORGHIU; Y. D. SONG

doi:10.1109/SSST.2004.1295621

Control of submarine operating in shallow waters: A neuro-adaptive based approach

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

^*Corresponding author for this work

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

Abstract

Neuro-adaptive control algorithms for depth and pitch control of submarine operating in shallow waters are presented in this paper. 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. Analyses and simulations show that the proposed control is effective in dealing with external disturbances, system nonlinearities, uncertainties and parameter variations.

Original language	English
Title of host publication	Proceedings of the Thirty-Sixth Southeastern Symposium on System Theory (SSST04)
Publisher	IEEE
Pages	69-73
Number of pages	5
ISBN (Print)	0780382811
DOIs	https://doi.org/10.1109/SSST.2004.1295621
Publication status	Published - 19 Jul 2004
Externally published	Yes
Event	Thirty-Sixth Southeastern Symposium on System Theory - Atlanta, United States Duration: 16 Mar 2004 → 16 Mar 2004

Symposium

Symposium	Thirty-Sixth Southeastern Symposium on System Theory
Country/Territory	United States
City	Atlanta
Period	16/03/04 → 16/03/04

Keywords

Adaptive Neural Network
Nonlinear Systems
Shallow Water
Submarine
Tracking Control

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10.1109/SSST.2004.1295621

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title = "Control of submarine operating in shallow waters: A neuro-adaptive based approach",

abstract = "Neuro-adaptive control algorithms for depth and pitch control of submarine operating in shallow waters are presented in this paper. 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. Analyses and simulations show that the proposed control is effective in dealing with external disturbances, system nonlinearities, uncertainties and parameter variations.",

keywords = "Adaptive Neural Network, Nonlinear Systems, Shallow Water, Submarine, Tracking Control",

author = "GHEORGHIU, \{Medorian D.\} and SONG, \{Y. D.\}",

year = "2004",

month = jul,

day = "19",

doi = "10.1109/SSST.2004.1295621",

language = "English",

isbn = "0780382811",

pages = "69--73",

booktitle = "Proceedings of the Thirty-Sixth Southeastern Symposium on System Theory (SSST04)",

publisher = "IEEE",

note = "Thirty-Sixth Southeastern Symposium on System Theory ; Conference date: 16-03-2004 Through 16-03-2004",

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TY - GEN

T1 - Control of submarine operating in shallow waters: A neuro-adaptive based approach

AU - GHEORGHIU, Medorian D.

AU - SONG, Y. D.

PY - 2004/7/19

Y1 - 2004/7/19

N2 - Neuro-adaptive control algorithms for depth and pitch control of submarine operating in shallow waters are presented in this paper. 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. Analyses and simulations show that the proposed control is effective in dealing with external disturbances, system nonlinearities, uncertainties and parameter variations.

AB - Neuro-adaptive control algorithms for depth and pitch control of submarine operating in shallow waters are presented in this paper. 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. Analyses and simulations show that the proposed control is effective in dealing with external disturbances, system nonlinearities, uncertainties and parameter variations.

KW - Adaptive Neural Network

KW - Nonlinear Systems

KW - Shallow Water

KW - Submarine

KW - Tracking Control

UR - https://www.scopus.com/pages/publications/3042784514

U2 - 10.1109/SSST.2004.1295621

DO - 10.1109/SSST.2004.1295621

M3 - Conference paper (refereed)

AN - SCOPUS:3042784514

SN - 0780382811

SP - 69

EP - 73

BT - Proceedings of the Thirty-Sixth Southeastern Symposium on System Theory (SSST04)

PB - IEEE

T2 - Thirty-Sixth Southeastern Symposium on System Theory

Y2 - 16 March 2004 through 16 March 2004

ER -

Control of submarine operating in shallow waters: A neuro-adaptive based approach

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