Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81735
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Computing-
dc.creatorHuang, ZJ-
dc.creatorLiu, XZ-
dc.creatorWen, JY-
dc.creatorZhang, GC-
dc.creatorLiu, YH-
dc.date.accessioned2020-02-10T12:28:53Z-
dc.date.available2020-02-10T12:28:53Z-
dc.identifier.issn1687-8434-
dc.identifier.urihttp://hdl.handle.net/10397/81735-
dc.language.isoenen_US
dc.publisherHindawi Publishing Corporationen_US
dc.rightsCopyright© 2019 Zhijian Huang et al. is is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly citeen_US
dc.rightsThe following publication Huang, Z., Liu, X., Wen, J., Zhang, G., & Liu, Y. (2019). Adaptive navigating control based on the parallel action-network ADHDP method for unmanned surface vessel. Advances in Materials Science and Engineering, 2019, 7697143, 1-7 is available at https://dx.doi.org/10.1155/2019/7697143en_US
dc.titleAdaptive navigating control based on the parallel action-Network ADHDP method for unmanned surface vesselen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1-
dc.identifier.epage7-
dc.identifier.volume2019-
dc.identifier.doi10.1155/2019/7697143-
dcterms.abstractThe feedback PID method was mainly used for the navigating control of an unmanned surface vessel (USV). However, when the intelligent control era is coming now, the USV can be navigated more effectively. According to the USV character in its navigating control, this paper presents a parallel action-network ADHDP method. This method connects an adaptive controller parallel to the action network of the ADHDP. The adaptive controller adopts a RBF neural network approximation based on the Lyapunov stability analysis to ensure the system stability. The simulation results show that the parallel action-network ADHDP method has an adaptive control character and can navigate the USV more accurately and rapidly. In addition, this method can also eliminate the overshoot of the ADHDP controller when navigating the USV in various situations. Therefore, the adaptive stability design can greatly improve the navigating control and effectively overcome the ADHDP algorithm limitation. Thus, this adaptive control can be one of the intelligent ADHDP control methods. Furthermore, this method will be a foundation for the development of an intelligent USV controller.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAdvances in materials science and engineering, 25 Nov. 2019, v. 2019, 7697143, p. 1-7-
dcterms.isPartOfAdvances in materials science and engineering-
dcterms.issued2019-
dc.identifier.isiWOS:000501772200002-
dc.identifier.scopus2-s2.0-85076555533-
dc.identifier.eissn1687-8442-
dc.identifier.artn7697143-
dc.description.validate202002 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
Huang_Parallel_Action-Network_ADHDP.pdf1.54 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

101
Last Week
1
Last month
Citations as of Mar 24, 2024

Downloads

66
Citations as of Mar 24, 2024

SCOPUSTM   
Citations

4
Citations as of Mar 28, 2024

WEB OF SCIENCETM
Citations

4
Citations as of Mar 28, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.