Adaptive neural network‐based fault‐tolerant trajectory‐tracking control of unmanned surface vessels with input saturation and error constraints-Reference-Cited by-同舟云学术

Adaptive neural network‐based fault‐tolerant trajectory‐tracking control of unmanned surface vessels with input saturation and error constraints

Published:2019-07-30 Issue:5 Volume:14 Page:356-363
ISSN:1751-9578
Container-title:IET Intelligent Transport Systems
language:en
Short-container-title:IET Intelligent Transport Systems

Author:

Qin Hongde¹,Li Chengpeng¹,Sun Yanchao¹^ORCID

Affiliation:

1. Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering UniversityHarbin150001People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Law,Mechanical Engineering,General Environmental Science,Transportation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-its.2019.0221

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4. Fuzzy‐based optimal adaptive line‐of‐sight path following for underactuated unmanned surface vehicle with uncertainties and time‐varying disturbances;Mu D.D.;Math. Probl. Eng.,2018

5. Stabilization of underactuated surface vessels: a continuous fractional power control method;Zhang P.F.;Appl. Sci.,2018

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