A neural network based controller for underwater robotic vehicles

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.

References added. This is a slightly updated version of the work presented at the COBEM 2011 - 21st Congress of Mechanical Engineering, 2011, Natal Brazil