A Neural Predictive Controller For Underwater Robotic Applications

Abstract

Oceanographic exploration is one of the fast emerging applications of robotics. The design of Underwater Robotic Vehicles (URV’s), is as challenging as for land based ones. The dificulties in modelling an URV and its hazardous environment restrict the use of conventional controllers. In this paper the application of Neural networks (NNs) for the modelling and control of a prototype URV, which is an example of a system containing non-linearities, is described. A NN model is developed and then incorporated into a predictive control strategy which it is evaluated both in simulation and on-line. Results are shown for both the modelling and control of the system, including hybrid control strategies which combine neural predictive with conventional three term controllers.