Model predictive control of underwater gliders based on a one-layer recurrent neural network

Shan, Y; Yan, Z; Wang, J

Model predictive control of underwater gliders based on a one-layer recurrent neural network

Shan, Y Yan, Z

Wang, J

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Publication Type:: Conference Proceeding
Citation:: 2013 6th International Conference on Advanced Computational Intelligence, ICACI 2013 - Proceedings, 2013, pp. 328 - 333
Issue Date:: 2013-01-01

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Field	Value	Language
dc.contributor.author	Shan, Y	en_US
dc.contributor.author	Yan, Z https://orcid.org/0000-0003-3368-2100	en_US
dc.contributor.author	Wang, J	en_US
dc.date.issued	2013-01-01	en_US
dc.identifier.citation	2013 6th International Conference on Advanced Computational Intelligence, ICACI 2013 - Proceedings, 2013, pp. 328 - 333	en_US
dc.identifier.isbn	9781467363433	en_US
dc.identifier.uri	http://hdl.handle.net/10453/121062
dc.description.abstract	In this paper, a motion control problem for underwater gilders in longitudinal plane is considered. A recurrent neural network based model predictive control approach is developed. The model predictive control of underwater gliders is formulated as a time-varying constrained quadratic programming problem, which is solved by using a recurrent neural network called the simplified dual network in real-time. Simulation results are further presented to show the effectiveness and performance of the proposed model predictive control approach. © 2013 IEEE.	en_US
dc.relation.ispartof	2013 6th International Conference on Advanced Computational Intelligence, ICACI 2013 - Proceedings	en_US
dc.relation.isbasedon	10.1109/ICACI.2013.6748525	en_US
dc.title	Model predictive control of underwater gliders based on a one-layer recurrent neural network	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

In this paper, a motion control problem for underwater gilders in longitudinal plane is considered. A recurrent neural network based model predictive control approach is developed. The model predictive control of underwater gliders is formulated as a time-varying constrained quadratic programming problem, which is solved by using a recurrent neural network called the simplified dual network in real-time. Simulation results are further presented to show the effectiveness and performance of the proposed model predictive control approach. © 2013 IEEE.

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http://hdl.handle.net/10453/121062