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.
@article{arxiv.2205.13344,
title = {A neural network based controller for underwater robotic vehicles},
author = {Josiane Maria Macedo Fernandes and Marcelo Costa Tanaka and Raimundo Carlos Silvério Freire Júnior and Wallace Moreira Bessa},
journal= {arXiv preprint arXiv:2205.13344},
year = {2022}
}
Comments
References added. This is a slightly updated version of the work presented at the COBEM 2011 - 21st Congress of Mechanical Engineering, 2011, Natal Brazil