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

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

The unmanned surface vessel (USV) plays an important role in smart ocean. This study proposes an adaptive fault‐tolerant tracking control for USVs in the presence of input saturations and error constraints. A tan‐type barrier Lyapunov function is utilised for the error constraints and the neural net...

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Bibliographic Details
Main Authors: Hongde Qin, Chengpeng Li, Yanchao Sun
Format: Article
Language:English
Published: Wiley 2020-05-01
Series:IET Intelligent Transport Systems
Subjects:
USV
input saturation
error constraints
tan‐type barrier Lyapunov function
neural networks
adaptive technique
Online Access:https://doi.org/10.1049/iet-its.2019.0221

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