Neural network-based fault-tolerant control of underactuated surface vessels
type: Item
instance of: scholarly article
title: Neural network-based fault-tolerant control of underactuated surface vessels
zbMATH Open document ID: 1394.70063
DOI: 10.1155/2015/903759
author: Bong Seok Park
published in: Mathematical Problems in Engineering
publication date: 2018-08-27T00:00:00Z
review text: Summary: This paper addresses the problem of trajectory tracking of underactuated surface vessels (USVs) in the presence of thruster failure. Multilayer neural networks (MNNs) are employed to estimate the unknown model parameters and external disturbances. To design a fault-tolerant controller without a fault detection scheme, we use the Nussbaum gain technique. We introduce an additional control to resolve the difficulty arising from having fewer inputs than degrees-of-freedom. Further, an approach angle is proposed to track both a straight and curved path. Stability analysis and simulations are performed to demonstrate the effectiveness of the proposed scheme.
Mathematics Subject Classification ID: 70Q05
Mathematics Subject Classification ID: 93C40
zbMATH DE Number: 6927514
Wikidata QID: Q59120219
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2015/903759
OpenAlex ID: W1914510541
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description: scientific article; zbMATH DE number 6927514