A Hybrid Tracking Control Strategy for an Unmanned Underwater Vehicle Aided with Bioinspired Neural Dynamics

Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/31372

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DC Field	Value	Language
dc.contributor.author	Xu Z	-
dc.contributor.author	Yan T	-
dc.contributor.author	Yang SX	-
dc.contributor.author	Gadsden SA	-
dc.date.accessioned	2025-03-03T23:38:40Z	-
dc.date.available	2025-03-03T23:38:40Z	-
dc.date.issued	2022-09-03	-
dc.identifier.uri	http://hdl.handle.net/11375/31372	-
dc.subject	40 Engineering	-
dc.subject	46 Information and Computing Sciences	-
dc.subject	4007 Control Engineering, Mechatronics and Robotics	-
dc.subject	4602 Artificial Intelligence	-
dc.subject	4010 Engineering Practice and Education	-
dc.title	A Hybrid Tracking Control Strategy for an Unmanned Underwater Vehicle Aided with Bioinspired Neural Dynamics	-
dc.type	Article	-
dc.date.updated	2025-03-03T23:38:39Z	-
dc.contributor.department	Mechanical Engineering	-
dc.identifier.doi	https://doi.org/10.48550/arxiv.2209.01484	-
Appears in Collections:	Mechanical Engineering Publications

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