Work

A neural network based controller for underwater robotic vehicles

Year: 2022

Type: preprint

Abstract: Due to the enormous technological improvements obtained in the last decades it is possible to use robotic vehicles for underwater exploration. This work describes the development of a dynamic positioning system for remotely operated underwater vehicles based. The adopted approach is developed using Lyapunov Stability Theory and enhanced by a neural network based algorithm for uncertainty and disturbance compensation. The performance of the proposed control scheme is evaluated by means of numerical simulations.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2205.13344

Authors: Fernandes, Josiane Maria Macedo, Tanaka, Marcelo Costa, Júnior, Raimundo Carlos Silvério Freire, Bessa, Wallace Moreira

Language: English

Topic: Underwater Vehicles and Communication Systems

Subfield: Ocean Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: Deutscher Akademischer Austauschdienst, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico

OpenAlex ID: W4281729430

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