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

Yuan Shan, Zheng Yan, Jun Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2013 6th International Conference on Advanced Computational Intelligence, ICACI 2013 - Proceedings
PublisherIEEE Computer Society
Pages328-333
Number of pages6
ISBN (Print)9781467363433
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 6th International Conference on Advanced Computational Intelligence, ICACI 2013 - Hangzhou, Zhejiang, China
Duration: 19 Oct 201321 Oct 2013

Publication series

Name2013 6th International Conference on Advanced Computational Intelligence, ICACI 2013 - Proceedings

Conference

Conference2013 6th International Conference on Advanced Computational Intelligence, ICACI 2013
Country/TerritoryChina
CityHangzhou, Zhejiang
Period19/10/1321/10/13

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